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Abstract Background Spinal tuberculosis (STB) is a local manifestation of systemic infection caused by Mycobacterium tuberculosis, accounting for a significant proportion of joint tuberculosis cases. This study aimed to explore the diagnostic value of MRI combined with mannose-binding lectin (MBL) for STB. Methods 124 patients suspected of having STB were collected and divided into STB and non-STB groups according to their pathological diagnosis. Serum MBL levels were measured using ELISA and a Pearson analysis was constructed to determine the correlation between MBL and STB. ROC was plotted to analyze their diagnostic value for STB. All the subjects included in the study underwent an MRI. Results The sensitivity of MRI for the diagnosis of STB was 84.38% and specificity was 86.67%. The serum MBL levels of the patients in the STB group were significantly lower than the levels in the non-STB group. ROC analysis results indicated that serum MBL’s area under the curve (AUC) for diagnosis of STB was 0.836, with a sensitivity of 82.3% and a specificity was 77.4%. The sensitivity of MRI combined with MBL diagnosis was 96.61%, and the specificity was 92.31%, indicating that combining the two diagnostic methods was more effective than using either one alone. Conclusions Both MRI and MBL had certain diagnostic values for STB, but their combined use resulted in a diagnostic accuracy than either one alone.

ABSTRACT Introduction As a common malignancy, lung cancer has a relatively poor prognosis and a low survival rate. In recent years, ferroptosis, as an emerging filed, has great promise in the potential treatment of cancer. Brucea javanica oil (BJO) is often used to treat various cancers. Oleic acid (OA) is the main ingredient of BJO. In this study, we investigated the role and molecular mechanism of OA in lung cancer treatment by promoting ferroptosis. Methods In this study, A549 cells and H1299 cells were used for in vitro experiments, and a CCK‐8 test, scratch test, and MTT experiment were carried out. We examined reactive oxygen species (ROS), the JC‐1 probe, glutathione (GSH) expression, lipid peroxidation, SDC4 mRNA levels, and ACSL4, SLC7A11, GPX4, and SDC4 protein levels. Results The results showed that OA could inhibit the proliferation and migration of A549 cells and H1299 cells, SDC4 was a potential therapeutic target of OA against lung cancer, and OA treatment significantly inhibited the expression of SDC4 in A549 cells and H1299 cells. OA induces ferroptosis in A549 cells and H1299 cells, decreases GSH levels, increases lipid peroxidation levels, and decreases SDC4 mRNA expression; in addition, OA upregulates ACSL4 expression and decreases SLC7A11, GPX4, and SDC4 expression. Conclusion This study confirmed that OA could inhibit SDC4 expression and promote the occurrence of ferroptosis in A549 cells and H1299 cells through the GPX4/ACSL4 pathway, providing an effective basis for the use of drugs targeting ferroptosis in lung cancer treatment.

Abstract Textile wastewater is among the most polluted types of industrial waste. Wastewater treatment in the textile industry is notoriously difficult because of the use of complex chemicals and dyes in the textile production steps, and conventional methods are not enough to treat these. Textile wastewater, known for its high pollution levels, poses challenges for treatment due to complex chemicals and dyes. A comparative study was conducted on simple ozonation and catalytic ozonation (CO) using alum to degrade methylene blue (MB). The authors analyzed various factors like time, pH, catalyst loading and ozone dosages during the study. Results showed that catalytic activity in ozonation depends on pH and ozone flow. The maximum MB elimination was achieved at pH 6.6 and 200 V ozone flow. Scanning electron microscopy (SEM) was used to characterize the surface morphology of the catalyst, Fourier transform infrared spectroscopy (FTIR) was used to identify the important functional groups, and energy dispersive X-ray spectroscopy (EDS) was used to characterize the catalyst's elemental composition. Compared to simple ozonation, CO showed higher removal in the initial phase. Real textile wastewater analysis confirmed the effectiveness of alum catalysts in achieving significant removal of MB (87%) through this novel cost-efficient process. Graphical Abstract

Objective To understand the impact of chronic disease comorbidity on healthcare institution-seeking behavior of elderly people in China, and to provide a theoretical basis for optimizing healthcare order and enhancing the management capacity of primary care for chronic diseases. MethodsThe data on 4 508 elderly people aged ≥ 60 years in 25 provincial-level administrative divisions across China were collected from the China Family Panel Studies (CFPS) conducted in 2020. The Stata 17.0 statistical software was used to analyze the impact of chronic disease comorbidity on healthcare facility-seeking behavior of elderly people in China using the probit regression model and the propensity score matching (PSM) method. ResultsOf the 4 508 elderly people surveyed, 748 (16.59%) reported having chronic disease comorbidity (suffering from two or more chronic diseases); 2 536 (56.26%) and 1 972 (43.74%) reported seeking medical treatment at primary and non-primary healthcare institutions during past six months. After adjusting for predisposing factors (gender, age, education level, marital status), enabling factors (household registration type, monthly retirement pension, satisfaction with medical treatment, participation in medical insurance, emotional relationship with children, financial support from children, caregiving provided by children), and need factors (self-rated health status, changes in health conditions, physical discomfort in the past two weeks, the ability to take care of oneself), the results of probit regression analysis showed that the elderly people with comorbid chronic diseases were more inclined to seek medical treatment at non-primary healthcare institutions (β = – 0.130, 95% confidence interval: – 0.237 – – 0.022). The estimated values of average treatment effect on the treated (ATT) of chronic disease comorbidity on the healthcare institution selection of the elderly people were – 0.052, – 0.048, and – 0.047, respectively, based on matched propensity scores of predisposing, enabling, and need factors with K-nearest neighbor, kernel, and radius matching (all P < 0.05), indicating that chronic disease comorbidity can reduce the probability of elderly people seeking medical treatment at primary healthcare institutions. The heterogeneity test results showed that the impact of chronic disease comorbidity on females (ATT = – 0.078 – – 0.063, all P < 0.05) and the elderly people with a junior high school education or below (ATT = – 0.058 – – 0.052, all P < 0.05) was more significant, but there was no statistically significant difference in the impact on males and elderly people with a high school education or above (all P > 0.05). ConclusionChronic disease comorbidity may affect the selection of medical institutions for elderly people in China to some extent, and its influence differs by gender and education level of the elderly.

Abstract Background Quitting support from smokers’ partners can predict quit attempts and smoking abstinence but research on factors that predict such support has been limited. To add more evidence for partner support and the improved interventions for smoking cessation, we analyzed some new potential predictors of quitting support from smokers’ spouses. Method This cross-sectional study was conducted in in 2022 and 2023, selecting the students’ families in which fathers smoked and mothers didn’t smoke from grade 1–5 of 13 primary schools in Qingdao, China. Parents who met the criteria completed the online questionnaires and 1018 families were included in the analysis. We measured personal information related to smokers and their spouses such as age, education and nicotine dependence, and variables related to family and marital relationship such as family functioning, perceived responsiveness and power in decision-making of quitting smoking. Quitting support from smokers’ spouses was measured by Partner Interaction Questionnaire and generalized linear model was used to explore the potential predictors of partner support. Results In this study, the mean age of smokers was 39.97(SD = 5.57) and the mean age of smokers’ spouses was 38.24(SD = 4.59). The regression analysis showed that for smokers and their spouses, the older age groups showed the lower ratio of positive/negative support(P

Background: The Juan-Bi decoction (JBD) is a classic traditional Chinese medicines (TCMs) prescription for the treatment of rheumatoid arthritis (RA). However, the active compounds of the JBD in RA treatment remain unclear.Aim: The aim of this study is to screen effective compounds in the JBD for RA treatment using systems pharmacology and experimental approaches.Method: Botanical drugs and compounds in the JBD were acquired from multiple public TCM databases. All compounds were initially screened using absorption, distribution, metabolism, excretion, and toxicity (ADMET) and physicochemical properties, and then a target prediction was performed. RA pathological genes were acquired from the DisGeNet database. Potential active compounds were screened by constructing a compound–target–pathogenic gene (C-T-P) network and calculating the cumulative interaction intensity of the compounds on pathogenic genes. The effectiveness of the compounds was verified using lipopolysaccharide (LPS)-induced RAW.264.7 cells and collagen-induced arthritis (CIA) mouse models.Results: We screened 15 potentially active compounds in the JBD for RA treatment. These compounds primarily act on multiple metabolic pathways, immune pathways, and signaling transduction pathways. Furthermore, in vivo and in vitro experiments showed that bornyl acetate (BAC) alleviated joint damage, and inflammatory cells infiltrated and facilitated a smooth cartilage surface via the suppression of the steroid hormone biosynthesis.Conclusion: We screened potential compounds in the JBD for the treatment of RA using systems pharmacology approaches. In particular, BAC had an anti-rheumatic effect, and future studies are required to elucidate the underlying mechanisms.

IntroductionTuberculosis, caused by Mycobacterium tuberculosis complex (MTBC), remains a global health concern in both human and animals. However, the absence of rapid, accurate, and highly sensitive detection methods to differentiate the major pathogens of MTBC, including M. tuberculosis, M. bovis, and BCG, poses a potential challenge.MethodsIn this study, we have established a triplex droplet digital polymerase chain reaction (ddPCR) method employing three types of probe fluorophores, with targets M. tuberculosis (targeting CFP-10-ESAT-6 gene of RD1 and Rv0222 genes of RD4), M. bovis (targeting CFP-10-ESATs-6 gene of RD1), and BCG (targeting Rv3871 and Rv3879c genes of ΔRD1), respectively.ResultsBased on optimization of annealing temperature, sensitivity and repeatability, this method demonstrates a lower limit of detection (LOD) as 3.08 copies/reaction for M. tuberculosis, 4.47 copies/reaction for M. bovis and 3.59 copies/reaction for BCG, without cross-reaction to Mannheimia haemolytica, Mycoplasma bovis, Haemophilus parasuis, Escherichia coli, Pasteurella multocida, Ochrobactrum anthropi, Salmonella choleraesuis, Brucella melitensis, and Staphylococcus aureus, and showed repeatability with coefficients of variation (CV) lower than 10%. The method exhibits strong milk sample tolerance, the LOD of detecting in spike milk was 5 × 103 CFU/mL, which sensitivity is ten times higher than the triplex qPCR. 60 clinical DNA samples, including 20 milk, 20 tissue and 20 swab samples, were kept in China Animal Health and Epidemiology Center were tested by the triplex ddPCR and triplex qPCR. The triplex ddPCR presented a higher sensitivity (11.67%, 7/60) than that of the triplex qPCR method (8.33%, 5/60). The positive rates of M. tuberculosis, M. bovis, and BCG were 1.67, 10, and 0% by triplex ddPCR, and 1.67, 6.67, and 0% by triplex qPCR, with coincidence rates of 100, 96.7, and 100%, respectively.DiscussionOur data demonstrate that the established triplex ddPCR method is a sensitive, specific and rapid method for differentiation and identification of M. tuberculosis, M. bovis, and BCG.

This work investigates the nonlinear response of a conical premixed flame to dual-frequency excitation through experiments and G-equation analysis. In addition to the responses at excitation frequencies, f1 and f2, a notable flame response can also be identified at the difference frequency, fd. The fd response is particularly significant in the high-frequency regime, characterized by multiple wavelengths of both f1 and f2 on the flame front. This distinct behavior of difference-frequency response can be attributed to the spatial superposition of the intensified flame fluctuation waves at the two forcing frequencies. As the excitation enhances at either f1 or f2, the nonlinear effect suppresses the responses of the upper-part flame at both f1 and f2 while promoting the bulk flame response at fd. Based on a third-order expansion of the G-equation, it is shown that the nonlinear flame dynamics necessarily generate the observed interaction component when the flame is perturbed by dual-frequency excitations. The present results emphasize the importance of nonlinear flame dynamics in inducing flame responses at interaction frequencies, offering insights into thermoacoustic oscillations of multiple frequencies.

Objectives: We intend to develop a dual-modal dynamic contour-based instance segmentation method that is based on carotid artery and jugular vein ultrasound and its optical flow image, then we evaluate its performance in comparison with the classic single-modal deep learning networks. Method: We collected 2432 carotid artery and jugular vein ultrasound images and divided them into training, validation and test dataset by the ratio of 8:1:1. We then used these ultrasound images to generate optical flow images with clearly defined contours. We also proposed a dual-stream information fusion module to fuse complementary features between different levels extracted from ultrasound and optical flow images. In addition, we proposed a learnable contour initialization method that eliminated the need for manual design of the initial contour, facilitating the rapid regression of nodes on the contour to the ground truth points. Results: We verified our method by using a self-built dataset of carotid artery and jugular vein ultrasound images. The quantitative metrics demonstrated a bounding box detection mean average precision of 0.814 and a mask segmentation mean average precision of 0.842. Qualitative analysis of our results showed that our method achieved smoother segmentation boundaries for blood vessels. Conclusions: The dual-modal network we proposed effectively utilizes the complementary features of ultrasound and optical flow images. Compared to traditional single-modal instance segmentation methods, our approach more accurately segments the carotid artery and jugular vein in ultrasound images, demonstrating its potential for reliable and precise medical image analysis.

High-altitude UAVs (HA-UAVs) have emerged as vital components in 6G communication infrastructures, providing stable relays for telecommunications services above terrestrial and aerial disturbances. This paper explores the multifaceted roles of HA-UAVs in remote sensing, data relay, and telecommunication network enhancement. A Large Language Model (LLM) framework is introduced that dynamically predicts optimal HA-UAV connectivity for IoT devices, enhancing network performance and adaptability. The study emphasizes HA-UAVs’ operational efficiency, broad coverage, and potential to transform global communications, particularly in remote and underserved areas. Our proposed satellite-HA-UAV-IoT architecture with LLM optimization demonstrated substantial improvements, including a 25% increase in network throughput (from 20 Mbps to 25 Mbps at a 20 km distance), a 40% reduction in latency (from 25 ms to 15 ms), and a 28% enhancement in energy efficiency (from 0.25 μJ/bit to 0.18 μJ/bit), significantly advancing the performance and adaptability of next-generation IoT networks. These advancements pave the way for unprecedented connectivity and set the stage for future communication technologies.

Through the use of recycled aggregates, the construction industry can mitigate its environmental impact. A key consideration for concrete structural engineers when designing and constructing concrete structures is compressive strength. This study aims to accurately forecast the compressive strength of recycled aggregate concrete (RAC) using machine learning techniques. We propose a simplified approach that incorporates a two-layer stacked ensemble learning model to predict RAC compressive strength. In this framework, the first layer consists of ensemble models acting as base learners, while the second layer utilizes a random forest (RF) model as the meta-learner. A comparative analysis with four other ensemble learning models demonstrates the superior performance of the proposed stacked model in effectively integrating predictions from the base learners, resulting in enhanced model accuracy. The model achieves a low mean absolute error (MAE) of 2.599 MPa, a root mean squared error (RMSE) of 3.645 MPa, and a high R-squared (R2) value of 0.964. Additionally, a Shapley (SHAP) additive explanation analysis reveals the influence and interrelationships of various input factors on the compressive strength of RAC, aiding design and construction professionals in optimizing raw material content during the RAC design and production process.

Abstract Background Hepatocyte growth factor (HGF) is a peptide-containing multifunctional cytokine, which is overexpressed and/or activated in multiple malignancies and is reported to be associated with tumor development and inferior survival. At present, the role of HGF in small cell lung cancer (SCLC) has not been fully explored yet. Materials and methods The expression of HGF and its value in predicting survival in SCLC were explored from GEO database and in pan-cancer analysis. Furthermore, we detected the expression of HGF using tumor tissue and paired plasma samples from a validation cohort of 71 SCLC patients at our institute. Correlation between tumor and plasma HGF expression and the prognostic values were analyzed. Results GEO database analysis revealed that tumor tissue had lower HGF expression than paired normal tissue in SCLC. At our institute, immunohistochemical staining showed negative expression of HGF in tumor tissue of SCLC at our institute (47/47, 100%). The average baseline plasma HGF was 1.28 (range,0.42–4.35) ng/ml. However, plasma HGF was higher in SCLC patients with patients with N3, M1, liver metastasis (LM) and bone metastasis (BM) disease compared with those N0 − 2 (1.25 vs. 1.75 ng/mL, P = 0.000), M0 (1.26 vs. 1.63 ng/mL, P = 0.003), non-LM (1.32 vs. 2.06 ng/mL, P = 0.009), and non-BM (1.35 vs. 1.77 ng/mL, P = 0.047), respectively. Multivariate analysis revealed plasma HGF was an independent predictor for LM and prognostic factor of OS. Conclusion Our results revealed that plasma HGF rather than tumor HGF exhibited a potential role in predicting metastasis and survival in SCLC. Plasma HGF might be used as a non-invasive detecting and monitoring tool for SCLC.

Abstract The Schlafen (SLFN)11 gene has been implicated in various biological processes such as suppression of HIV replication, replication stress response, and sensitization of cancer cells to chemotherapy. Due to the rapid diversification of the SLFN family members, it remains uncertain whether a direct ortholog of human SLFN11 exists in mice. Here we show that mSLFN8/9 and hSLFN11 were rapidly recruited to microlaser-irradiated DNA damage tracks. Furthermore, Slfn8/9 expression could complement SLFN11 loss in human SLFN11 −/− cells, and as a result, reduced the growth rate to wild-type levels and partially restored sensitivity to DNA-damaging agents. In addition, both Slfn8/9 and SLFN11 expression accelerated stalled fork degradation and decreased RPA and RAD51 foci numbers after DNA damage. Based on these results, we propose that mouse Slfn8 and Slfn9 genes may share an orthologous function with human SLFN11. This notion may facilitate understanding of SLFN11’s biological role through in vivo studies via mouse modeling.

Abstract Aerial base stations (AeBSs), as crucial components of air-ground integrated networks, are widely employed in cloud computing, disaster relief, and various applications. How to quickly and efficiently deploy multi-AeBSs for higher capacity gain has become a key research issue. In this paper, we address the 3D deployment optimization problem of multi-AeBSs with the objective of maximizing system capacity. To overcome communication overhead and privacy challenges in multi-agent deep reinforcement learning (MADRL), we propose a federated deep deterministic policy gradient (Fed-DDPG) algorithm for the multi-AeBS deployment decision. Specifically, a high-altitude platform (HAP)-assisted multi-AeBS deployment architecture is designed, in which low-altitude AeBS act as the local nodes to train its own deployment decision model, while the HAP acts as the global node to aggregate the weights of local models. In this architecture, AeBSs do not exchange raw data, addressing data privacy concerns and reducing communication overhead. Simulation results show that the proposed algorithm outperforms fully distributed MADRL algorithms and closely approximates the performance of multi-agent deep deterministic policy gradient (MADDPG), which requires global information during training, but with less training time.

Abstract Acute lung injury (ALI) is an adverse disease of the respiratory system, and one of its prevalent causes is sepsis induction. Cell pyroptosis facilitates the progression of ALI and lncRNAs play critical roles in ALI. Thus, this research seeks to investigate the specific mechanism of NEAT1 in sepsis‐ALI.BEAS‐2B cells were exposed to lipopolysaccharide (LPS) to construct a cell model of sepsis‐induced ALI. The gene and protein expression were assessed using qRT‐PCR and western blot. Cell viability was identified by CCK‐8. Cell death was discovered using PI staining. The secretion of IL‐1β and IL‐18 was examined using ELISA. The interconnections among NEAT1, miR‐26a‐5p, and ROCK1 were confirmed using starbase, luciferase assay, and RIP.LPS treatment augmented NEAT1 and ROCK1 levels while mitigating miR‐26a‐5p level in BEAS‐2B cells. Additionally, LPS treatment facilitated cell death and cell pyroptosis, whereas NEAT1 silencing could reverse these effects in BEAS‐2B cells. Mechanistically, NEAT1 positively mediated ROCK1 expression by targeting miR‐26a‐5p. Furthermore, miR‐26a‐5p inhibitor offset NEAT1 depletion‐mediated suppressive effects on cell death and cell pyroptosis. ROCK1 upregulation decreased the inhibitory impacts produced by miR‐26a‐5p overexpression on cell death and cell pyroptosis. Our outcomes demonstrated NEAT1 could reinforce LPS‐induced cell death and cell pyroptosis by repressing the miR‐26a‐5p/ROCK1 axis, thereby worsening ALI caused by sepsis. Our data indicated NEAT1, miR‐26a‐5p, and ROCK1 might be biomarkers and target genes for relieving sepsis‐induced ALI.

In the context of “dual carbon” goals, governments need accurate carbon accounting results as a basis for formulating corresponding emission reduction policies. Therefore, this study proposes a combined carbon emission prediction method for urban regions, considering micro-level enterprise electricity consumption data and macro-level regional data. Considering the different applicability of prediction methods and the requirements for the data volume, a region-level carbon emission prediction method based on the long short-term memory neural network is proposed, which takes into account the micro-level electricity–carbon coupling relationship. Additionally, a region-level carbon emission prediction method based on the Stochastic Impacts by Regression on Population, Affluence, and Technology (STIRPAT) is proposed, considering the macro-level economic–carbon coupling relationship. The generalized induced ordered weighted averaging method is employed to assign differential weights to micro- and macro-prediction values, yielding regional carbon emission predictions. An empirical analysis is conducted using a key city in the eastern region as an example, analyzing the main influencing factors and predicting carbon emissions based on relevant data from 2017 to 2021, and the accuracy of the models is analyzed and validated.

Introduction: This study aimed to investigate the impact of a 10-week Core Stability Training (CST) compared to Traditional Strength Training (TST) on the balance abilities of adolescent male basketball players.Methods: Subjects (age: 15.70 ± 0.75, height: 178.4 ± 8.31, weight: 66.55 ± 8.34) were randomly assigned to either the Core Stability Training group or the Traditional Strength Training group. Three selected balance assessment indicators included the Single-leg Standing with Eyes Closed Test, Star Excursion Balance Test, and Core Four-Direction Endurance Test.Results: 1) The scores were significantly different in both groups before and after the Single-leg Standing with Eyes Closed Test; (p < 0.01, d = 1.692, d = 1.837); 2) In the Star Excursion Balance Test, the scores of the experimental group showed significant difference (p < 0.05) or highly significant difference (p < 0.01) with an average effect size of (d = 1.727) when the left or right foot supported in the other directions before and after the training. However, there was no significant difference in scores in the c direction when the left foot supported (p > 0.05, d = 0.954); 3) In the Core Four-Direction Endurance Test, there were no significant differences in scores for the control group before and after training (p > 0.05, d = 0.567), while the experimental group showed significant differences in scores before and after training (p < 0.05, d = 1.889).Discussion: Both CST and TST were effective in enhancing the balance abilities of adolescent basketball players. CST, in particular, demonstrated improvements in dynamic balance and agility across multiple planes. Basketball coaches are encouraged to consider incorporating CST training programs into their overall training plans for optimal balance enhancement.

Idiopathic pulmonary fibrosis (IPF) is a fatal interstitial lung disease with an unclear pathogenesis. This study aimed to elucidate the function and potential mechanisms of TUG1 in IPF progression. Cell viability and migration were detected by CCK-8 and transwell assays. Autophagy, fibrosis, or EMT-related proteins were measured by Western blotting. Pro-inflammatory cytokine levels were assessed by ELISA kits. The subcellular localization of TUG1 was observed by FISH assay. RIP assay detected the interaction between TUG1 and CDC27. TUG1 and CDC27 was up-regulated in TGF-β1-induced RLE-6TN cells. TUG1 depletion suppressed pulmonary fibrosis via attenuating inflammation, EMT, inducing autophagy and inactivating PI3K/Akt/mTOR pathway in vitro and in vivo. TUG1 knockdown prevented CDC27 expression. TUG1 silencing ameliorated pulmonary fibrosis by reducing CDC27 expression and inhibiting PI3K/Akt/mTOR pathway.

Abstract Background Nicotine dependence is a significant public health issue, and understanding the factors associated with nicotine dependence in this population is crucial for developing effective interventions. This study examined the association between family functioning and nicotine dependence levels of smoking fathers based on the McMaster model of family functioning (MMFF), providing evidence for future interventions. Methods In this study, we selected fathers of first- to fifth-grade students from 10 pilot elementary schools in Qingdao whose families smoked. We used the Fagerstrom test to assess nicotine dependence and the Family Assessment Device to evaluate family functioning. We performed univariate analysis to compare differences among those with different levels of nicotine dependence, and we used an ordinal logistic regression analysis to investigate the influences related to nicotine dependence. Results This study included 874 smokers, with 78.5% having mild nicotine dependence, 11.7% having moderate dependence, and 9.84% having severe dependence. Univariate analysis showed that smokers with severe dependence had lower education levels, higher prevalence of chronic diseases, more frequent alcohol consumption, and poorer family functioning compared to those with mild to moderate dependence. Ordinal logistic regression analysis showed that poorer general functioning scores (OR = 1.087, 95% CI: 1.008–1.173, P = 0.030), poorer behavioral control (OR = 1.124, 95% CI: 1.026–1.232, P = 0.012), more quit attempts, frequent alcohol consumption, and longer smoking duration may be associated with a higher likelihood of developing severe nicotine dependence. The older age of starting smoking and higher education level may be associated with a lower likelihood of developing severe nicotine dependence. However, it is important to note that the cross-sectional nature of this study precludes the determination of causal relationships. Conclusions This study finds that heavy nicotine dependence in smoking fathers is associated with risky behaviors and demographics such as longer smoking duration and frequent alcohol consumption. Targeted smoking cessation interventions are crucial for this group, taking these specific factors into consideration. Family functioning, particularly general functioning and behavioral control, may also be linked to nicotine dependence, indicating the need for further research in this area.

Accurate wind power forecasting (WPF) is critical in optimizing grid operations and efficiently managing wind energy resources. Challenges arise from the inherent volatility and non-stationarity of wind data, particularly in short-to-medium-term WPF, which extends to longer forecast horizons. To address these challenges, this study introduces a novel model that integrates Improved Empirical Mode Decomposition (IEMD) with an enhanced Transformer called TransIEMD. TransIEMD begins by decomposing the wind speed into Intrinsic Mode Functions (IMFs) using IEMD, transforming the scalar wind speed into a vector form that enriches the input data to reveal hidden temporal dynamics. Each IMF is then processed with channel attention, embedding, and positional encoding to prepare inputs for an enhanced Transformer. The Direct Embedding Module (DEM) provides an alternative viewpoint on the input data. The distinctive perspectives of IEMD and DEM offer interaction through cross-attention within the encoder, significantly enhancing the ability to capture dynamic wind patterns. By combining cross-attention and self-attention within the encoder–decoder structure, TransIEMD demonstrates enhanced proficiency in detecting and leveraging long-range dependencies and dynamic wind patterns, improving the forecasting precision. Extensive evaluations on a publicly available dataset from the National Renewable Energy Laboratory (NREL) demonstrate that TransIEMD significantly improves the forecasting accuracy across multiple horizons of 4, 8, 16, and 24 h. Specifically, at the 24 h forecast horizon, TransIEMD achieves reductions in the normalized mean absolute error and root mean square error of 4.24% and 4.37%, respectively, compared to the traditional Transformer. These results confirm the efficacy of integrating IEMD with attention mechanisms to enhance the accuracy of WPF.

Introduction Diabetic foot ulcer (DFU) stands as a severe diabetic lower extremity complication, characterized by high amputation rates, mortality, and economic burden. We propose using Mendelian randomization studies to explore shared and distinct risk factors for diabetic lower extremity complications.Research design and methods We selected uncorrelated genetic variants associated with 85 phenotypes in five categories at the genome-wide significance level as instrumental variables. Genetic associations with DFU, diabetic polyneuropathy (DPN), and diabetic peripheral artery disease (DPAD) were obtained from the FinnGen and UK Biobank studies.Results Body mass index (BMI) emerged as the only significant risk factor for DPAD, DPN, and DFU, independent of type 2 diabetes, fasting glucose, fasting insulin, and HbA1c. Educational attainment stood out as the sole significant protective factor against DPAD, DPN, and DFU. Glycemic traits below the type 2 diabetes diagnosis threshold showed associations with DPAD and DPN. While smoking history exhibited suggestive associations with DFU, indicators of poor nutrition, particularly total protein, mean corpuscular hemoglobin, and mean corpuscular volume, may also signal potential DFU occurrence.Conclusions Enhanced glycemic control and foot care are essential for the diabetic population with high BMI, limited education, smoking history, and indicators of poor nutrition. By focusing on these specific risk factors, healthcare interventions can be better tailored to prevent and manage DFU effectively.

With the increasing scarcity of spectrum resources and the continuous exploration of high-frequency spectrum resources, millimeter wave (mmWave) has been introduced to 5G deployment scenarios, one of which is the high-speed railway wireless networks. Because of the characteristics of mmWave, it is suitable for Enhanced Mobile Broadband (eMBB) service in subway tunnel scenarios, in which there are increasing data rate requirement of passengers to be satisfied. To this end, we propose a new scheme of Integrated Access and Backhaul (IAB) plus small stations in the carriage, in which the backhaul link is 5G Non-Standalone (NSA) networking with 4G for master node and 5G mmWave for secondary node, so as to overcome the handover burden and penetration loss of mmWave, that is more severe in the high-frequency range. Based on the existing old 4G equipment, mmWave is applied for 5G user-plane connection in NSA dual connection, while the control plane connection still relies on 4G commercial frequency band, in order that even if the millimeter-wave link quality is seriously degraded, the IAB-node can still maintain the connection with the master node and re-establish the mmWave link through the exchange of control information on the 4G low-frequency band. Unlike previous attempts, the proposed approach applies dual link to the backhaul link and 5G commercial frequency band to the in-vehicle access link of small station with Radio Access Network (RAN) sharing technology, so that the bandwidth shared by the operators can be aggregated in one small station and fully used for user access to match the mmWave large bandwidth of the backhaul link. Field trials showed that although the data rates were somewhat unstable at the handover points, which still need to be improved in the future work, the average end-to-end uplink and downlink data rates were greatly improved, compared to the previous average data rates when only outdoor signal penetrating indoors was used in subway tunnel. In addition, the proposed scheme can reduce the operator’s construction and maintenance costs by making full use of the existing 4G equipment, which provides a reference for upgrading 4G to 5G signal coverage for all tunnel scenarios.

The irrigation water effective utilization coefficient (IWEUC) is a critical indication of agricultural water use efficiency. To improve water-saving potential, the inter-annual variation of IWEUC from 2014 to 2021 in Jiangsu Province was analyzed. Taking consideration of natural factors, planting structure, management levels, and water-saving engineering, the primary influencing factors of IWEUC were investigated through principal component analysis. The results revealed that IWEUC in Jiangsu Province was higher than the annual national level and showed an insignificant increasing trend. IWEUC and its trend were negatively correlated with irrigation district size. Water-saving irrigation areas had an extremely significant impact on IWEUC (P < 0.01). The positive load of water-saving engineering investment was rated first. Furthermore, economic and water-saving benefits for different irrigation district scales based on the TOPSIS model were evaluated. Despite restricted government support, the economic gains for large irrigation districts were superior to those for small irrigation districts. In the past decade, agricultural water declined while agricultural water conservation rose. The completion of integrated agricultural water pricing reform, as well as the improvement of water-saving engineering and optimization of management level, had a significant beneficial influence on IWEUC. Jiangsu's IWEUC has been efficiently implemented, and provides guidelines in other regions. HIGHLIGHTS The inter-annual fluctuation of irrigation water effective utilization coefficient in Jiangsu Province in recent years is comprehensively introduced.; Dominant factors affecting irrigation water effective utilization coefficient through principal component analysis are analyzed.; Economic and water-saving benefits for different irrigation district scales based on the TOPSIS model are evaluated.;

Gallium-modified HZSM-5 zeolites demonstrate increased selectivity towards aromatics during methanol conversion, but the mechanism and the nature of the active sites that lead to this enhanced selectivity are poorly understood. Here, in situ synchrotron radiation photoionization mass spectrometry experiments reveal that increased formaldehyde generation over Ga2O3 species plays a key role in promoting the production of aromatic compounds.

Abstract Background Circulating tumor DNA (ctDNA) has been proven to be a promising tumor-specific biomarker in solid tumors, but its clinical utility in risk stratification and early prediction of relapse for diffuse large B cell lymphoma (DLBCL) has not been well explored. Methods Here, using a lymphoma-specific sequencing panel, we assessed the prognostic and predictive utilities of ctDNA measurements before, during, and after first-line therapy in 73 Chinese DLBCL patients. Results The pretreatment ctDNA level serving as an independent prognostic factor for both progression-free survival (PFS, adjusted HR 2.47; p = 0.004) and overall survival (OS, adjusted HR 2.49; p = 0.011) was confirmed in our cohort. Furthermore, the patients classified as molecular responders who presented a larger decrease in ctDNA levels after the initial two treatment cycles had more favorable PFS (unreached vs. 6.25 months; HR 5.348; p = 0.0015) and OS (unreached vs. 25.87; HR 4.0; p = 0.028) than non-responders. In addition, interim ctDNA clearance may be an alternative noninvasive method of positron emission tomography and computed tomography (PET-CT) for predicting better PFS (HR 3.65; p = 0.0033) and OS (HR 3.536; p = 0.016). We also demonstrated that posttreatment ctDNA was a sensitive indicator for detecting minimal residual disease (MRD) in patients with a high risk of recurrence (HR 6.471; p = 0.014), who were otherwise claimed to achieve radiographic CR (complete remission). Conclusions CtDNA is a promising noninvasive tool for prognosis prediction, response assessment, and early relapse prediction of first-line treatment in DLBCL patients.

With the development of coal chemical technology, a large amount of gasification slag and wastewater are produced through coal gasification. Efficient gasification slag utilization and wastewater treatment have attracted much attention. In this study, gasification slag was modified and used as a low-cost and efficient catalyst to activate persulfate for acetaminophen degradation. Via the analysis of high-resolution X-ray photoelectron spectroscopy, the surfaces of nitric acid and calcined modified gasification slag retained a considerable number of carbonyl and graphite N functional groups. These proved to be effective active sites for the activation of persulfate. X-ray diffraction analysis revealed that the gasification slag was composed of carbon and SiO2. The evaluation of catalytic activity and application of density functional theory proved that the interaction between carbonyl and graphitic nitrogen significantly affected the catalyst activity. When the ratio of graphitic nitrogen to carbonyl was 1:3, the adsorption and activation of persulfate were significantly enhanced. The results of the quenching experiments also confirmed that the non-free radical pathway is the main pathway to activate persulfate using the gasification slag. This study provides a new approach to industrial waste utilization in wastewater treatment.

Modification of catalysts by multi-heteroatom doping (S, P, B) is an effective way to improve the peroxomonosulfate activation performance of catalysts. In recent years, highly toxic and persistent trace organic contaminants have been frequently detected in water. Consequently, we proposed the advanced oxidation processes of peroxomonosulfate activated by multi-heteroatom doped Fe@CN (X-Fe@CN) to eliminate trace organic contaminants. The physical phases of X-Fe@CN and its precursors were characterized by X-ray diffraction and scanning electron microscopy. In evaluating the catalytic properties and iron ion leaching of X-Fe@CN-activated PMS for the removal of dicamba and atenolol, B-Fe@CN and PB-Fe@CN were selected and optimized. The active sites of the catalysts were characterized by X-ray photoelectron spectroscopy and Raman. The pathways of PMS activation by B-Fe@CN and PB-Fe@CN were identified in combination with electron paramagnetic resonance and electrochemical experiments. Defects, O-B-O and pyrrolic nitrogen on the surface of B-Fe@CN could adsorb and activate PMS to produce SO4•−, ·OH and 1O2. Further doping with P enhanced the electron transfer on the catalyst surface, thus accelerating the activation of peroxomonosulfate. This study compared the effects of multi-heteroatom modifications and further demonstrated the synergistic effect between P and B, which can provide a theoretical basis for the selection of multi-heteroatom doped catalysts in water treatment.

Background: The D-isoforms of amino acids (D-AAs) exhibit anti-biofilm potential against a diverse range of bacterial species in vitro, while its role in vivo remains unclear. The aim of this study was to investigate the effects of a combination of D-AAs and vancomycin on a PJI rat model. Methods: Eight-week-old male SD rats were randomized to the control group, sham group, vancomycin group, D-AAs–vancomycin group. After treatment for 6 weeks, we analysed the levels of inflammatory factors in serum, behavioural change, imaging manifestations. The anti-biofilm ability of D-AAs was detected by crystal violet staining and scanning electron microscope observation, and its ability to assist antibiotics in killing bacteria was assessed by culture of bacteria. Additionally, micro-CT and histological analysis were used to evaluate the impact of D-AAs combined with vancomycin on the bone remodelling around the prosthesis. Results: The group treated with a D-AAs–vancomycin combination sustained normal weight gain and exhibited reduced the serum levels of α2M, IL-1β, IL-6, IL-10, TNF-α and PGE2. Moreover, treated with D-AAs in combination with vancomycin improved the weight-bearing activity performance, increased the sizes and widths of distal femurs, and improved Rissing scale scoring. In particular, treatment using D-AAs enhanced the ability of vancomycin to eradicate Staphylococcus aureus, as demonstrated by the dispersion of existing biofilms and the inhibition of biofilm formation that occurred in a concentration-dependent manner. This treatment combination also resulted in a reduction in bacterial burden with in the soft tissues, bones, and implants. Furthermore, D-AAs–vancomycin combination treatment attenuated abnormal bone remodelling around the implant, as evidenced by an observed increase in BMD, BV/TV, and Tb.Th and the presence of reduced Trap+ osteoclasts and elevated osterix+ osteo-progenitors. Conclusions: Combining D-AAs with vancomycin provides an effective therapeutic strategy for the treatment of PJI by promoting biofilm dispersion to enhance antimicrobial activity.

Abstract Background Under the outbreak of Coronavirus disease 2019 (COVID-19), a structural equation model was established to determine the causality of important factors that affect Chinese citizens’ COVID-19 prevention behavior. Methods The survey in Qingdao covered several communities in 10 districts and used the method of cluster random sampling. The research instrument used in this study is a self-compiled Chinese version of the questionnaire. Of the 1215 questionnaires, 1188 were included in our analysis. We use the rank sum test, which is a non-parametric test, to test the influence of citizens’basic sociodemographic variables on prevention behavior, and the rank correlation test to analyze the influencing factors of prevention behavior. IBM AMOS 24.0 was used for path analysis, including estimating regression coefficients and evaluating the statistical fits of the structural model, to further explore the causal relationships between variables. Results The result showed that the score in the prevention behavior of all citizens is a median of 5 and a quartile spacing of 0.31. The final structural equation model showed that the external support for fighting the epidemic, the demand level of health information, the cognition of (COVID-19) and the negative emotions after the outbreak had direct effects on the COVID-19 prevention behavior, and that negative emotions and information needs served as mediating variables. Conclusions The study provided a basis for relevant departments to further adopt epidemic prevention and control strategies.

Research on the spatial–temporal pattern of the supply and demand associated with ecosystem services(ESs) is of great significance for regional sustainable development. Due to their high spatial heterogeneity, the relationship between supply and demand of ESs in mountainous areas in particular needs to be further studied. This paper examines the supply and demand of ESs in the Taihang Mountains from 2000 to 2018 at both the whole-region and county scale to evaluate supply–demand patterns, the nature and resilience of the supply–demand relationship, and to analyze spatiotemporal variation and characteristics, which can provide a basis for the coordination and sustainable management of the supply and demand relationship of the ecosystem. Our results showed that during the study period: （1)the ecosystem services supply(ESS) increased by 2.36% and the ecosystem services demand(ESD) increased by 50.93%,the increase in the rate of ESS was far less than that of ESD and on the county scale, the ESS of 20% of the counties decreased whereas and the ESD of all counties increased.（2)the supply and demand pattern of the Taihang Mountains remained basically unchanged，the types of supply and demand in the Taihang Mountains are mainly low supply-high demand, low supply-low demand, and high supply-low demand, accounting for>90% of the total county number.（3)the average supply and demand index of high altitude counties is more than five times that of low altitude counties.The average supply and demand index of counties with low economic growth rate is twice that of the high economic growth rate.（4)67% of counties reduced the resilience level of total ecosystem services（TES), the resilience level of the provisioning services(PS) decreased most significantly, reaching 76%.

Background: The prognostic factors and optimal choice of treatment for primary neuroendocrine neoplasms of the breast (BNEN) remain to be defined. Methods: Patients diagnosed with BNEN in China were retrospectively reviewed from the literature following the systematic search of China National Knowledge Infrastructure (CNKI), Chinese biomedical literature service system (sinomed), wanfang medical network, and Pubmed database. The clinical characteristics and different treatment modalities of patients with BNEN were evaluated. Results: A total of 209 cases with BNEN were enrolled. There were 204 female and 5 male patients. The median age was 51 years old (range, 17–82). Out of 209 patients with BNEN, 208 (99.5%) patients were treated with surgery (SG), 44 patients (21.1%) had received radiotherapy (RT), 173 patients (82.8%) experienced chemotherapy (CT). A total of 158 patients with hormone receptor (HR) positive (87.8%, 158/180) were treated with endocrine treatment (ET). The median follow-up time was 52.4 months (range, 6–144). The 3-year overall survival (OS) rate and 3-year disease-free survival (DFS) rate for the whole group were 93.7% and 85.3%, respectively. In univariate analyses, Ki67 expression ≥20%, HR negative, neuroendocrine carcinomas (NECs) were associated with decreased OS and DFS (P 0.05). Conclusions: The best selection of patients to get the most benefit from different treatment modalities warrant further exploration. The clinicopathological parameters including gender, HR expression, ki67 expression, pathologic type, stage, tumor size, and lymph node status may serve as both indicators of diagnosis and prognosis, and guide treatment decisions for BNEN.

The genome composition of intermediate wheatgrass (IWG) is complex and continues to be a subject of investigation. In this study, molecular cytogenetics were used to investigate the karyotype composition of Th. intermedium and its relative diploid species. St2-80 developed from Pseudowroegneria strigose and pDb12H developed from Dasypyrum breviaristatum were used as probes in fluorescence in situ hybridization (FISH) to classify the chromosomes of Th. intermedium into three groups, expressed as JvsJvsJrJrStSt. A combined multiplex oligonucleotide probe, including pSc119.2-1, (GAA)10, AFA-3, AFA-4, pAs1-1, Pas1-3, pAs1-4, and pAs1-6, was used to establish the FISH karyotype of ten accessions of Th. intermedium. Variability among and within the studied accessions of intermediate wheatgrass was observed in their FISH patterns. Results of this study led to the conclusions that Jvs had largely been contributed from Da. breviaristatum, but not the present-day Da. villosum; IWG had only one J genome, Jr, which was related to either Th. elongatum or Th. bessarabicum; and St was contributed from the genus Pseudoroegneria by hybridization with Th. junceiforme or Th. sartorii.

This paper explores the advancements of drones in the context of sixth-generation mobile communication technology (6G) green Internet of Things (IoT) through the utilization of digital twin (DT) technology within unmanned aerial vehicle (UAV) networks. We propose a framework for DT-based UAV applications in the realm of green IoT, where distinct tasks within the digital twin interact with physical-world UAVs through task manager scheduling. We characterize the radio frequency (RF) attributes of the DT using three-dimensional (3D) millimeter-wave (mmWave) radar imaging on UAVs. The wireless channel modeling, based on ray tracing, underscores the alignment of RF domains between the DT and the physical UAV in a bid to take advantage of multipath reflections and save communication energy. Our numerical findings have justified the efficacy of the drone-enabled DT platform in achieving accurate RF representation of UAVs for the intelligent operation and management of IoT-based green UAV networks.

The hypoxia-inducible factor-1α/endoplasmic reticulum stress signaling pathway (HIF-1α/ERS) has a crucial role in the pathogenetic mechanism of pulmonary fibrosis (PF). However, the upstream regulatory mediators of this pathway remain unclear. In the present study, by conducting bioinformatics analysis, we found that Krüppel-like factor 4 (KLF4) expression was decreased in the lung tissues of patients with idiopathic pulmonary fibrosis (IPF) as compared to that in patients with non-IPF. Furthermore, KLF4 expression was significantly reduced (p = 0.0331) in bleomycin-induced fibrotic HFL-1 cells. Moreover, in mice with bleomycin-induced PF, the degree of fibrosis was significantly reduced in mice overexpressing KLF4 as compared to that in wild-type mice. In mice and HFL-1 cells, KLF4 overexpression significantly reduced bleomycin-induced protein expression of HIF-1α (p = 0.0027) and ERS markers, particularly p-IRE1α (p = 0.0255) and ATF6 (p = 0.0002). By using the JASPAR database, we predicted that KLF4 has five binding sites for the HIF-1α promoter. The results of in vitro and in vivo studies suggest that KLF4 may inhibit PF through the HIF-1α/ERS pathway. This finding could guide the development of future therapies for PF and facilitate the identification of appropriate biomarkers for routine clinical diagnosis of PF.

The High-Altitude Platform Station (HAPS) is an integral component in Non-Terrestrial Network (NTN) which is potential 6G technology. The HAPS as IMT Base Stations (HIBS) in the mobile service is an emerging and promising approach to achieve vertical heterogeneous network. Therefore, some efforts have been made in order to harmonize the worldwide usage of HIBS, including investigations of the spectrum needs, usage, and technical and operational characteristics of HIBS, among which the spectrum needs has drawn particular attention because it should be determined in advance prior to the commercial deployment of HIBS. However, there are very few investigations devoted to the prediction of the spectrum needs for future HIBS deployments currently due to some tough difficulties. Firstly, there has no actual deployment precedent of HIBS so that the future capacity demands are not clear. Secondly, both the networking and its performance of HIBS deployment are questions to be answered. Therefore, taking into account the study under WRC-23 Agenda Item 1.4 HIBS-CHARACTERISTICS, this paper proposes an evaluation method of the spectrum needs prediction for HIBS deployed as a supplementary for grounded base station, and presents the results of spectrum needs for HIBS in certain frequency bands identified for IMT. The capacity demand of HIBS in 2025 is predicted and the spectral efficiency of HIBS system is obtained by simulation, and the spectrum needs is defined as Capacity Demand/Spectral Efficiency. The main contributions of this paper are as follows: Firstly, to obtain the spectral efficiency of HIBS systems, we set up a simulation model with 7-cell networking in accordance with configuration parameters of WRC-23 AI 1.4, which equipped with beamforming antenna to improve spectral efficiency. And calculating the CDF curve of spectral efficiency by using Monte Carlo method allows the simulation result to more closely match the actual deployment. Secondly, in order to solve the problem of no actual HIBS traffic data, we propose a method based on the methodology provided in Recommendation ITU-R M.1768-1 to simulate the capacity demand, and then to predict the capacity demand of HIBS in 2025 by polynomial fitting. Finally, we have predicted the spectrum needs by calculating Capacity Demand/Spectral Efficiency. The spectrum demand range of HIBS for China rural area in 2025 predicted by the proposed method is from 80.30 MHz to 122.97 MHz. This method can effectively predict the spectrum needs of HIBS for various deployment scenarios, which plays an important role in driving the commercial deployment of HIBS.

Smoke-free government(SFG), as a key tobacco control measure, has been added in Healthy China 2030 blueprint and Qingdao started the establishment of the demonstrative SFG in 2020.This study examined the effects of SFG policy on smoking and smoke-free(SF) environment after establishing the demonstrative SFG. This cross-sectional survey selected participants by simple random sampling from party and government agencies in Qingdao (N = 3625) and the participants filled in questionnaires online from November 31 to December 15, 2020. We utilized AMOS to set up models to analyze the direct and indirect effects of SFG policy. The findings showed that knowledge of SFG policy was positively associated with SF environment(β = 0.29, P

Pancreatic cancer (PC) is a malignant tumor with high malignancy that is difficult to diagnose and treat. PC is a major medical problem because of its low early diagnosis rate, high surgical mortality rate, low cure rate, and expensive related testing cost. Therefore, the significance of finding new markers for PC is self-evident. Semaphorins (Semas) have been shown to affect angiogenesis and lymphangiogenesis and can also directly affect the behavior of tumor cells. The expression and related action targets of its family members on PC are summarized in this review.

Abstract 6G technology connects physical and digital, and ubiquitous 6G services will provide convenience to users around the world. The concept of the world-earth integrated network is to seamlessly integrate these three subnets to better adapt to future development. This article introduces the world-earth integrated network and shape-adaptive IRS antenna technology. The shape-adaptive IRS antenna described in this article is made of flexible materials, and the physical shape of the antenna can be changed according to different situations, and specific radiation beams can be generated according to functional requirements. And the effectiveness of the shape-adaptive IRS antenna technology has been proven in the simulation results.

The pathogenic microorganisms in the air have a significant impact on piglet growth and even biosecurity of pig industry. Carbon felt-based microbial adsorption shows great potential in reducing the misuse of chemical disinfectants in pig houses. However, poor biocompatibility and low adsorption efficiency hinder the application of carbon felt for microbial control in animal husbandry. Herein, modified carbon felt was prepared with strong acid to improve its surface properties and internal structure. The hydrophilic and large specific surface area of modified sample offered high adsorption activity for bacteria adhered on biotic/abiotic interface. Fourier transform infrared spectrometer, X-ray diffraction, pore specific surface area analysis, and scanning electron microscopy were used to analyze the chemical functional groups and microporous structure of the modified carbon felt. Antibacterial tests were performed using the model bacteria Escherichia coli. Acid treatment converts the hydrophobicity of carbon felt to hydrophilicity, increasing adsorption capacity and promoting a disinfection rate of up to 97.3%. This study can enhance bioaffinity and adsorption selectivity of carbon felt to Escherichia coli, bringing its antibacterial activity and application prospects closer to industrialization.

In recent years, immune checkpoint inhibitors (ICIs), represented by PD-1/PD-L1 monoclonal antibodies, have become a research hotspot in the field of oncology treatment. Immunotherapy has shown significant survival advantages in a variety of solid tumors. However, the phenomenon of hyperprogressive disease (HPD) in some patients treated with immunotherapy is gradually getting more attention and focus. An early understanding of the characteristics of HPD is crucial to optimize the treatment strategy. We report a patient with unresectable stage III lung adenocarcinoma who developed HPD with metastasis during consolidation therapy with durvalumab after chemoradiation. To further investigate the potential mechanism of HPD after anti-PD-L1 treatment, primary lung baseline tissue, baseline plasma, post-immunotherapy plasma, and liver metastasis samples of the patient were detected via next-generation sequencing (NGS). Then, multiplex immunohistochemistry (mIHC) was performed on primary lung baseline tissue and liver metastasis samples. KRAS and p.G12C were identified as the major driver mutation genes. With a low tumor mutation burden (TMB) value, the patient presented a very high percentage of CD8+PD-L1+ T cells that infiltrated in the baseline tissue, with 95.5% of all CD8+ cells expressing PD-L1 and a low percentage of CD8+ T cells expressing PD-1. After the emergence of HPD from immunotherapy, liver metastases were similarly infiltrated with an extremely high proportion of CD8+PD-L1+ T cells, with 85.6% of all CD8+ cells expressing PD-L1 and almost no CD8+ T cells expressing PD-1. The extreme infiltration of PD-L1+CD8+ T cells in the tumor microenvironment of baseline tissue might be associated with the aggressive tumor growth observed in anti-PD-L1 treatment for related HPD and could be a potential biomarker for HPD development.

This study aims to investigate the decolourization efficiency of reactive black 5 (RB-5) dye by using CuMn2O4/gC3N4 coated zeolites (zeolite 4A) for the first time in a hybrid electro-flocculation-catalytic ozonation process. A comparison between various treatment options such as electro-flocculation, electro-flocculation in the presence of a catalyst, and catalytic ozonation in combination with electro-flocculation was explored. Moreover, the effect of different factors such as pH, time, catalyst dose, ozone dose, radical scavenger, and voltage has been studied in each treatment option mentioned earlier. The results indicated that the best treatment option was found to be catalytic ozonation in combination with electro-flocculation with removal efficiency (RE) of 90.31% at pH 10 after 30 min of the treatment process. The hydroxyl radical scavenger effect indicated that the synergistic catalytic process follows a radical mechanism. It is therefore concluded that CuMn2O4/gC3N4–zeolite catalysts in synergic electro-flocculation-catalytic ozonation process may be effectively used for the treatment of textile wastewaters. HIGHLIGHTS The present research explores the CuMn2O4/gC3N4 coated Zeolites performance for the removal of RB5 in synergic processes.; A comparison of synergic processes was studied.; The synergic electro-flocculation catalytic ozonation process showed the highest RB5 removal efficiency of 90.31%.; The work concludes the effective application of CuMn2O4/gC3N4 coated zeolites for the treatment of textile wastewater.;

Varicella is a contagious disease of children. Qingdao administrated free one-dose and free two-dose universal varicella vaccination schedules in 2013 and 2016 for preschool children. The effectiveness of the vaccination was analyzed in this study. Monthly varicella incidence data of 1–6 years old children during 2007–2020 were obtained from the Qingdao Infectious Disease Reporting Information Management System. We applied Interrupted time series and segmented regression analyses to assess changes in varicella incidence at the beginning of each month and average monthly changes during the vaccination. The vaccination was associated with a reduction of 32.7% in varicella morbidity on average during the 8-year intervention, there is a statistically significant difference between the voluntary period and free vaccination period (χ2 = 290.80,P

Abstract With exceptional performance, flexible sensors have found broad applications, including human health monitoring, motion detection, human–machine interaction, smart wearable technology, and robot control. Crack‐sensitive structures based on animal bionics have also caught increasing attention because of their extraordinary sensitivity. Crack‐based flexible sensors, which combine the flexibility of the flexible sensors and the high sensitivity of the crack sensing structures, have seen rapid development in recent years. In this review, we summarize the sensing mechanisms of the flexible sensors based on the crack disconnection–reconnection process. The effects of crack type, depth, and density on sensor performance are explored in detail. We also discuss the performance characteristics and applications of the crack‐based flexible sensors with various materials, design structures, and crack generation procedures. Finally, the main challenges of the crack‐based flexible sensors are also reviewed, and several research directions are proposed.

In this research, the efficiency of the catalytic activity of iron and manganese-loaded (bimetallic) sodium zeolite was investigated for the ozonation-based removal of disperse yellow 42 dye. The impregnation method was used to deposit Fe and Mn on the surface of sodium zeolite. The morphological analysis of sodium zeolite before and after Fe and Mn deposition was conducted by SEM, EDX, and FTIR. It was found that several variables, including the ozone dose, contact time, pH, catalyst dose, and hydroxyl radical scavenger action, greatly influenced the efficiency of dye removal. The chemical oxygen demand (COD) removal by catalytic ozonation using Fe and Mn-loaded sodium zeolite from real dye textile wastewater was also investigated. After 30 min of treatment with catalytic ozonation at pH 6, the maximum 73% removal of disperse yellow 42 dye was achieved with a catalyst dose of 0.5 g and an ozone dose supply of 1.8 mg/min. In catalytic ozonation with the hydroxyl radical scavenger effect (HRSE), the decline in removal efficiency from 73% to 61% demonstrated that removal efficiency was highly dependent on hydroxyl radical production. The COD removal efficiency in the real textile wastewater was 59% with the ozonation process, which increased to 79% after catalytic ozonation.

The environment in livestock and poultry houses plays an important role in the growth and reproduction of livestock and poultry. In order to obtain the environmental conditions of livestock and poultry houses in a timely and reliable manner, and eliminate adverse environmental factors, scholars have been exploring various methods to obtain and predict environmental factors. This paper reviewed the literature from the last 10 years, specifically focusing on technologies for detecting environmental factors in livestock and poultry houses, which can be mainly divided into three categories: research on the environmental monitoring and control of livestock and poultry houses based on detection equipment and wireless sensor technology; research on the distribution and regularity of environmental factors in livestock and poultry houses based on a mathematical model; research on the environmental simulation and detection of livestock and poultry houses based on computer technology. The current testing methods have their advantages and disadvantages. When studying environmental factors, researchers should choose the most appropriate method for data acquisition according to the actual situation. The proposed recommendations for achieving this goal are as follows: (1) The control of environmental factors should be combined with the physiological response of livestock and poultry. The needs of animals should be considered; (2) Novel approaches need to be developed to integrate energy requirements into the environmental regulation of livestock and poultry houses; (3) It is necessary to research and develop control models and strategies that can predict the environment in the houses, and the transient simulation method should be further explored; (4) Improve environmental detection and control accuracy through the coupling of different technologies.

Lignin valorization via thermochemical approaches has the potential to produce renewable fuels and value-added chemicals, which are of great significance to the sustainable development of human beings. During the thermochemical depolymerization which involves acid-catalyzed, alkali-catalyzed, oxidative, reductive, pyrolytic, and other reactions, the lignin structure will undergo a series of bond cleavage, condensation, and functional group changes, while the mechanism is still unclear. To improve the efficiency, the analysis of the evolution of intermediates during depolymerization is very important, among which soft ionization mass spectrometry plays a vital role. This review aims to summarize the research progress of process analysis of lignin depolymerization in both gas-phase, typically thermal and catalytic pyrolysis, and liquid-phase via online mass spectrometry. The challenges and our insights into the future development of the lignin valorization as well as soft ionization mass spectrometry methods are also discussed.

Abstract Introduction Type 2 diabetes mellitus (T2DM) is a chronic disease with a high incidence worldwide. T2DM can cause cognitive impairment, but its neuropathological basis is unclear. A variety of neuropsychiatric studies have found that abnormal functional connectivity (FC) in the central executive network (CEN), default‐mode network (DMN), and salience network (SN) may be the neuropathological basis of cognitive dysfunction. The right dorsal anterior insula (dAI) is the core SN area. It plays an important role in regulating the CEN and the DMN. However, few studies have explored the relationship between cognitive impairment and FC among the right dAI, CEN, and DMN in patients with T2DM. Methods Resting‐state functional magnetic resonance imaging was used to investigate FC between the right dAI and the CEN and DMN in 44 patients with T2DM and 41 sex‐, age‐, and education‐matched healthy controls, as well as its relationship with clinical/cognitive variables. Results In patients with T2DM, FC between the right dAI and multiple brain regions of the CEN and DMN was generally decreased, and FC strength between the right dAI and the inferior frontal gyrus negatively correlated with trail making test A score (r = −0.421, p = 0.004). Conclusions Patients with T2DM exhibit abnormal FC between the right dAI and the CEN and DMN. This may be one of the neuromechanisms of cognitive impairment in patients with T2DM. In addition, reduced FC between the right dAI and the right inferior frontal gyrus may be related to abnormal attention regulation in patients with T2DM.

BackgroundChronic insomnia disorder (CID) is a highly prevalent sleep disorder, which influences people's daily life and is even life threatening. However, whether the resting-state regional homogeneity (ReHo) of disrupted brain regions in CID can be reshaped to normal after treatment remains unclear.MethodsA novel intervention real-time functional magnetic resonance imaging neurofeedback (rtfMRI-NF) was used to train 28 CID patients to regulate the activity of the left amygdala for three sessions in 6 weeks. The ReHo methodology was adopted to explore its role on resting-state fMRI data, which were collected before and after training. Moreover, the relationships between changes of clinical variables and ReHo value of altered regions were determined.ResultsResults showed that the bilateral dorsal medial pre-frontal cortex, supplementary motor area (SMA), and left dorsal lateral pre-frontal cortex had decreased ReHo values, whereas the bilateral cerebellum anterior lobe (CAL) had increased ReHo values after training. Some clinical scores markedly decreased, including Pittsburgh Sleep Quality Index, Insomnia Severity Index, Beck Depression Inventory, and Hamilton Anxiety Scale (HAMA). Additionally, the ReHo values of the left CAL were positively correlated with the change in the Hamilton depression scale score, and a remarkable positive correlation was found between the ReHo values of the right SMA and the HAMA score.ConclusionOur study provided an objective evidence that amygdala-based rtfMRI-NF training could reshape abnormal ReHo and improve sleep in patients with CID. The improved ReHo in CID provides insights into the neurobiological mechanism for the effectiveness of this intervention. However, larger double-blinded sham-controlled trials are needed to confirm our results from this initial study.

Depolymerization of lignin can yield phenolic monomeric platform molecules, but depolymerization and repolymerization are proposed as concurrent processes, which greatly limit the yield of monomeric products. Molecular-level characterization of heavy intermediates during depolymerization process is crucial for developing efficient methods to depolymerize raw lignin into monomers. In this study, a reactor-integrated negative-ion electrospray ionization high-resolution mass spectrometry was used to real-time analyze the lignin depolymerization process under operando conditions. Elemental composition, structural information as well as time-resolved evolution of a series of dimers and oligomers were obtained, which is hard to achieve with traditional GC-MS methods. The real-time evolution profiles of monomers, dimers, and oligomers reveals a possible repolymerization process during lignin depolymerization. These results provide insight into the complex lignin depolymerization process.

Ralph Krafczyk et al. demonstrate that both proline codon usage and prolyl-tRNA abundance affect mRNA translation rates of polyproline-motifs in bacteria. These results provide additional insight into sequence-specific translation regulation.