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Excessive heavy metal content in soil can seriously hinder plant physiological metabolism and growth. This study, with soybean, examined how drip irrigation reduced heavy metal toxicity. The drip irrigation experiments with four irrigation frequencies were conducted by controlling the lower limit of the soil matric potential (D1: −10 kPa; D2: −20 kPa; D3: −30 kPa; D4: −40 kPa). Through comparison with traditional surface irrigation, the effects of drip irrigation on heavy metal distribution, soybean growth status, physiological metabolism and transcriptome under Cd, Pb and Cr(VI) composite pollution were comprehensively analyzed. The results show that (i) The Cd, Pb and Cr(IV) in soil migrated away from the plant under drip irrigation, thereby reducing the inhibition of heavy metal stress on soybean growth at the root, among which D1 had the best improvement effect on soybean growth. (ii) Drip irrigation improved the resistance of soybean to heavy metal stress, and promoted the transport and fixation of free Cd2+, Pb2+ and Cr6+ in cells, thereby reducing the damage of oxidative stress and heavy metal ions to cell structure. (iii) Drip irrigation was conducive to the energy supply and protein stability of cell physiological metabolism, which helped the improvement of soybean physiological activity. Overall, compared with surface irrigation, drip irrigation reduced the toxicity of heavy metals to soybeans by moving heavy metals out of the root zone and enhancing physiological activity. The results of this study can provide a theoretical basis for the application of drip irrigation technology in the prevention and control of heavy metal pollution, and provide a new strategy for the safe production of agriculture.

Background: Prophylactic antibacterial drugs are used for patients with liver cirrhosis and upper gastrointestinal bleeding, and independent studies have concluded that they can decrease the rate of infection, mortality, and rebleeding in these diseases. However, no comprehensive assessment of this effect has been reported in recent years and available data pertaining to the prognostic implications of diverse categories of antibiotic prophylaxis in individuals afflicted with cirrhosis are notably limited. The objective of this article is to assess the clinical effectiveness of prophylactic antibacterial drugs for patients with liver cirrhosis and upper gastrointestinal bleeding.Methods: Relevant randomized controlled studies and cohort studies which examined the value of prophylactic antibacterial drugs for patients with liver cirrhosis and upper gastrointestinal bleeding were retrieved via Cochrane Library, EMBASE, MedLine, and Web of Science. The search period was from database inception until 30 April 2023. Summing up the relevant data, the dichotomous variable was statistically analysed using the relative risk (RR) value and its 95% confidence interval (CI) and the continuous variable using the mean difference (MD) value and its 95% CI. All analyses were performed using Revman 5.4 software. The study has been registered on the PROSPERO website under registration number CRD42022343352.Results: Twenty-six studies (18 RCTs and 8 cohort studies, including 13,670 participants) were included to evaluate the effect of antibacterial prophylaxis versus no antibacterial prophylaxis or placebo. Prophylactic antibiotics reduced mortality rates (RR 0.66, 95% CI 0.51–0.83), infection rates (RR 0.41, 95% CI 0.35–0.49), rebleeding rates (RR 0.42, 95% CI 0.31–0.56), and length of hospital stay (MD −5.29, 95% CI −7.53, −3.04). Subgroup analysis revealed that the prophylactic administration of quinolone antimicrobials demonstrated the most favorable efficacy, followed by cephalosporins. Both interventions were effective in averting infections frequently observed in patients with liver cirrhosis and upper gastrointestinal bleeding.Conclusion: Based on our investigation, the prophylactic antibacterial drugs confers noteworthy advantages in patients afflicted by liver cirrhosis with upper gastrointestinal bleeding. It has been associated with reductions in mortality, infection incidence, rebleeding occurrences, and the duration of hospitalization. Among prophylactic antibacterial options, quinolones emerged as the foremost choice, with cephalosporins ranking closely thereafter.Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42022343352, identifier CRD42022343352.

This study proposes a novel honey bee dancing (HBD) maximum power point tracking (MPPT) algorithm inspired by the foraging behavior of honey bees. When a bee finds nectar, it returns to the honeycomb and dances to inform others about the location of the nectar. Other bees then fly towards the location and gather the nectar. The proposed HBD algorithm uses five bees searching for the nectar who communicate with each other about the location and the quantity of nectar by dancing. Finally, the five bees found the location of the most nectar which is represented by the maximum power point. The proposed HBD algorithm applies to uniform irradiance condition (UIC) and partial shaded condition (PSC). It is then compared with the PV panel output power and load relationship (OPLR) algorithm and perturb and observe (P&O) algorithm. Experimental verification has been performed under both the UIC and PSC. At the UIC's irradiance level of 200 W/m2, the PV module's output power for the proposed HBD algorithm, OPLR algorithm, and P&O algorithm are 120 W, 118 W, and 94.5 W, respectively, with efficiencies of 99 %, 97 %, and 78 %. Additionally, under the PSC with an irradiance level of 600 W/m2, the PV module's output power for the proposed HBD algorithm, OPLR algorithm, and P&O algorithm are 218 W, 189.2 W, and 74.8 W, respectively, with efficiencies of 99 %, 86 %, and 34 %, and convergence times of 4.7 ms, 6.5 ms, and 6 ms, respectively. It is evident from the results that the solar MPPT performance of the proposed HBD algorithm is better than the OPLR algorithm and P&O algorithm. This method ingeniously combines the foraging behavior of bees with solar power generation to produce the maximum natural power. This approach does not require the development of photovoltaic (PV) panel specification data, complex calculations, and additional temperature meters and heliographs. It is highly efficient and has significant economic benefits.

Background: Quantum image processing is rapidly developing in the field of quantum computing, and it can be successfully implemented on the Noisy Intermediate-Scale Quantum (NISQ) device. Quantum image encryption holds a pivotal position in this domain. However, the encryption process often encounters security vulnerabilities and entails complex computational complexities, thereby consuming substantial quantum resources. To address this, the present study proposes a quantum image encryption algorithm based on four-dimensional chaos.Methods: The classical image is first encoded into quantum information using the Generalized Quantum Image Representation (GQIR) method. Subsequently, the trajectory of the four-dimensional chaotic system is randomized, and multi-dimensional chaotic keys are generated to initially encrypt the pixel values of the image. Then, the Arnold transformation is applied to randomly encrypt the pixel positions, resulting in the encrypted image. During the decryption process, the inverse process of encryption is employed to restore the original image.Results: We simulated this process in the Python environment, and the information entropy analysis experiment showed that the information entropy of the three encrypted images reached above 7.999, so the system has good encryption. At the same time, the correlation of the pixel distribution after the encryption algorithm is weak, which proves that the control parameters of the chaotic system can effectively reduce the correlation between pixels in the image. In the final key space analysis, the key space issued by our encryption can reach $10140\gg 2128$.Conclusion: Our method is resistant to destructive attacks and can produce scrambled images with higher encryption and usability. This algorithm solves the problems of general encryption algorithms such as periodicity, small key space, and vulnerability to statistical analysis, and proposes a reliable and effective encryption scheme. By making full use of the characteristics of Arnold transformation permutation, ergodicity and the randomness of the four-dimensional chaotic system, the encryption algorithm uses the larger key space provided by the four-dimensional Lorenz system.

BackgroundChanges in the gut microbiota are closely related to insomnia, but the causal relationship between them is not yet clear.ObjectiveTo clarify the relationship between the gut microbiota and insomnia and provide genetic evidence for them, we conducted a two-sample Mendelian randomization study.MethodsWe used a Mendelian randomized two-way validation method to discuss the causal relationship. First, we downloaded the data of 462,341 participants relating to insomnia, and the data of 18,340 participants relating to the gut microbiota from a genome-wide association study (GWAS). Then, we used two regression models, inverse-variance weighted (IVW) and MR-Egger regression, to evaluate the relationship between exposure factors and outcomes. Finally, we took a reverse MR analysis to assess the possibility of reverse causality.ResultsThe combined results show 19 gut microbiotas to have a causal relationship with insomnia (odds ratio (OR): 1.03; 95% confidence interval (CI): 1.01, 1.05; p=0.000 for class. Negativicutes; OR: 1.03; 95% CI: 1.01, 1.05; p=0.000 for order.Selenomonadales; OR: 1.01; 95% CI: 1.00, 1.02; p=0.003 for genus.RikenellaceaeRC9gutgroup). The results were consistent with sensitivity analyses for these bacterial traits. In reverse MR analysis, we found no statistical difference between insomnia and these gut microbiotas.ConclusionThis study can provide a new direction for the causal relationship between the gut microbiota (class.Negativicutes, order.Selenomonadales, genus.Lactococcus) and insomnia and the treatment or prevention strategies of insomnia.

This work investigates the chemical effects of ethane, propane, and butane substitution for methane on flame properties and sooting behaviors in inverse diffusion flames of natural gas in different ratios by a decoupling method. Results show that the influences of varying natural gas ratios on the concentration distributions of soot particles and soot gaseous precursors are greater than on temperature. After a certain amount of methane is replaced by C2–C4 alkanes, the soot volume fraction (SVF) becomes more centerline-dominated. Meanwhile, the average primary particle diameter increases while the number density of primary particles and the average number of primary particles per aggregate decrease. Due to their chemical effects, C2–C4 alkanes not only promote the formation of H2, C2H2, and C4H4 but also contribute to an increase in A2, A3, and A4 formation. As for the soot formation reaction rates, the condensation rates are promoted. However, under varying ratios, C2–C4 alkanes demonstrate diverse chemical effects on the coagulation rates. Among three alkanes, ethane has the most pronounced chemical suppression effect on soot inception, HACA surface growth, and oxidation process rates. The combined effects of increased condensation and delayed oxidation rates result in elevated SVF in natural gas flames.

In future fusion reactors, W-Cu joining technology will be utilized to fabricate plasma facing components (PFCs). In this study, hydrogen isotope gas-driven permeation (GDP) and thermal desorption spectrometry (TDS) are performed for W-Cu, W and Cu samples to understand the impact of W-Cu joining on fuel transport. GDP results reveal that the diffusion activation energy of the W-Cu sample is 0.289 eV, significantly smaller than that of the reference sample. Compared with the reference sample, the deuterium (D) retention in the W-Cu sample is doubled. High resolution transmission electron microscope (HRTEM) images indicate the presence of a mixed region of about 20 nm at the W-Cu interface, with a dislocation density in this region of 7.38 × 1016 m−2, three orders of magnitude higher than that in W and Cu. Simultaneously, energy dispersive spectrometer (EDS) data show that significant oxygen (O) impurities within the mixed region. Results from first principles simulations suggest that the presence of O at the interface can significantly alter the formation energy of H. The mixed layer not only serves as a diffusion barrier but also has the capacity to capture D. The presence of a high number of dislocations and O impurities in the mixed layer greatly impacts D transport in the W-Cu component.

Ultrasonic electrodeposition was employed to manufacture ZnCo2O4 anode nanomaterials (ZCOAN), with the objective of utilization as high-performance anode materials for lithium-ion batteries. The influence of ultrasonic power on various characteristics of ZCOAN, including surface morphology, phase composition, crystal structure, and electrochemical properties was also investigated. The results indicated that ZnCo2O4 anode nanomaterials prepared at 600 W demonstrated a spinel surface structure with polyporous dendrite spores and a subcrystalline size of 11.68 nm. Moreover, the prepared ZCOAN material demonstrated polyporous morphological characteristics and well-organized particles. Diffraction peaks were identified at specified angles in all ZCOAN samples: 31.26°, 36.93°, 46.38°, 54.13°, 59.87°, and 66.17° corresponding to the crystallographic planes (200), (311), (400), (422), (511), and (440), respectively. The appearance of these peaks confirms the presence of a spinel structure in the ZCOAN samples. A smaller grain size results in increased gaps and a larger surface area, thereby promoting ion exchange. Therefore, ZnCo2O4 anode nanomaterials synthesized at 600 W showed superior electrochemical performance compared to other samples. They demonstrated the highest charge capacity (∼1176 mAh·g−1), discharge capacity (∼1160 mAh·g−1), and stability, along with a minimal electrical impedance (35.65 Ω) at a constant current density of 150 mA·g−1. Furthermore, the coulomb efficiency of this nanomaterial remained high at 98.6 % after 1200 cycles, indicating its excellent cycling performance.

Salt stress is one of the major impairments to agricultural soil that significantly reduces growth and productivity in rice (Oryza sativa L.) and other crop plants. The proteomic mechanisms underlying salt stress tolerance in rice have not been well established. Therefore, a comprehensive understanding of molecular mechanisms associated with salt signaling, salt-toxicity detoxification, and other metabolic mechanisms is essential for elucidating salt tolerance mechanisms in rice as well as ensuring global food security. Recent proteome studies have provided a global proteomic signature of rice cultivars. Integrative studies of proteomic, physiological, and molecular responses under salt stress have provided detailed mechanisms associated with salt stress tolerance in rice. This review explores the proteomic mechanisms with finely-tuned salt-responsive networks in this cereal. Several proteomic processes, including salt sensing and signaling, scavenging of reactive oxygen species (ROS) and stress defense, salt compartmentalization and homeostasis, alterations of cell wall components, modulation of the cytoskeleton, regulation of salt-responsive genes, transcription factors, and protein synthesis, protein folding and processing, protein degradation, and strategies of carbohydrate and energy metabolism for organ development, elucidate extensive molecular mechanisms linked to salt stress responses and tolerance in rice. Further, it is updated the prospects of salt stress tolerance in rice using multi-omics and CRISPR/Cas approaches. These finely-tuned molecular insights will be beneficial to rice breeders and farmers for developing high-yielding, salt-tolerant rice cultivars to achieve global food security.

Chronic Pseudomonas aeruginosa (PA) infection significantly contributes to morbidity and mortality in bronchiectasis patients. Initiating antibiotics early may lead to the eradication of PA. Here we outline the design of a trial (ERASE; NCT06093191) assessing the efficacy and safety of inhaled tobramycin, alone or with oral ciprofloxacin, in bronchiectasis patients with a new isolation of PA. This multicentre, 2×2 factorial randomised, double-blind, placebo-controlled, parallel-group trial includes a 2-week screening period, a 12-week treatment phase (with a combination of ciprofloxacin or a placebo at initial 2 weeks) and a 24-week follow-up. 364 adults with bronchiectasis and a new PA isolation will be randomly assigned to one of four groups: placebo (inhaled saline and ciprofloxacin placebo twice daily), ciprofloxacin alone (750 mg ciprofloxacin and inhaled saline twice daily), inhaled tobramycin alone (inhaled 300 mg tobramycin and ciprofloxacin placebo twice daily) or a combination of both drugs (inhaled 300 mg tobramycin and 750 mg ciprofloxacin twice daily). The primary objective of this study is to assess the proportion of patients successfully eradicating PA in each group by the end of the study. Efficacy will be evaluated based on the eradication rate of PA at other time points (12, 24 and 36 weeks), the occurrence of exacerbations and hospitalisations, time to first pulmonary exacerbations, patient-reported outcomes, symptom measures, pulmonary function tests and the cost of hospitalisations. To date no randomised trial has evaluated the benefit of different PA eradication strategies in bronchiectasis patients. The ERASE trial will therefore generate crucial data to inform future clinical guidelines.

Construction and demolition waste (CDW) was fully exploited to prepare high-strength and low-cost unfired bricks. A compound additive consisting of sodium silicate, microsilica powder, an early-strength water reducer, and wood fiber was incorporated into the bricks. Tests (compressive tests, freeze–thaw cycle tests, and scanning electron microscopy (SEM)) were carried out to determine the effect of the contents of the additive components on the properties (the strength, softening coefficient, freezing resistance, hydration products, and microscopic morphology) of unfired bricks of different curing ages. The experimental results were used to determine the optimum ratio of the components and the hydration mechanism. The optimized compound additive considerably improved the mechanical properties and crack resistance of the bricks, where the optimum content was found to be only 3.15% of the CDW dry mass. Compared with unfired bricks with no additives, unfired bricks with the optimized compound additive exhibited increases in the 1- and 28-day compressive strengths and softening coefficient of up to 66.8%, 65.9%, and 8.46%, respectively (corresponding to values of 8.46 MPa, 29.36 MPa, and 0.934, respectively) and a decrease in the freeze–thaw strength loss rate of 61.38%. Incorporating the compound additive into the unfired bricks considerably reduced the environmental impact. The SEM micrographs showed that the compound additive increased the silicon-to-calcium ratio and workability of the preparation mixture, increased the hydration rate, promoted the conversion of calcium hydroxide in the product to a C–S–H gel, and enhanced the density and strength of the hydration product.

Background: Rising evidence indicates the development of pyroptosis in the initiation and pathogenesis of spinal cord injury (SCI). However, the associated effects of pyroptosis-related genes (PRGs) in SCI are unclear. Methods: We obtained the gene expression profiles of SCI and normal samples in the GEO. Database: The R package limma screened for differentially expressed (DE) PRGs and performed functional enrichment analysis. Mechanical learning and PPI analysis helped filter essential PRGs to diagnose SCI. Peripheral blood was collected for validation from ten SCI patients and eight healthy individuals. The association of essential PRGs with immune infiltration was evaluated, and pyroptosis subtypes were recognized in SCI patients by unsupervised cluster analysis. Besides, a SCI model was built for in vivo validation of essential PRGs. Result: We identified 25 DE-PRGs between SCI and normal controls. Functional enrichment analysis revealed the principal involvement of DE-PRGs in pyroptosis, inflammasome complex, interleukin-1 beta production, etc. Subsequently, three essential PRGs were identified and validated, showing excellent diagnostic efficacy and significant correlation with immune cell infiltration. Additionally, we developed diagnostic nomograms to predict the occurrence of SCI. Two pyroptosis subtypes exhibited distinct biological functions and immune landscapes among SCI patients. Finally, the expression of these essential PRGswas verified in vivo. Conclusion: The current study described the vital effects of pyroptosis-related genes in SCI, providing a novel direction for effective assessment and management of SCI.

For some engineering application, accurately estimating reliability only depend on the history data or failure mechanism is difficult to implement, due to the lack of data and imperfect theory of failure mechanism. Namely, both history data and failure mechanism should be utilized to improve the reliability estimation accuracy for engineering applications. Hence, we construct a reliability estimation method by fusing the failure mechanism and artificial neural network (ANN) supported Wiener processes for utilizing both history data and failure mechanism. ANN and failure mechanism are integrated into Wiener process with random effects, respectively. Bayesian model averaging (BMA) method is adapted to combine the failure mechanism with ANN supported Wiener processes, as well as to update the model parameters by fusing data. Based on a typical aviation hydraulic pump's actual dataset, we illustrate the advantages of our approach by comparing to Wiener process supported only by ANN or failure mechanism in engineering practices. The proposed method shows superiorities on reliability estimation considering the estimation accuracies comparing the other two models.

BackgroundAlthough clinical studies have revealed a potential link between Helicobacter pylori (H. pylori) infection and irritable bowel syndrome (IBS), the causal relationship between them remains unknown. The objective of this study was to investigate whether H. pylori infection is causally associated with IBS.MethodA two-sample Mendelian randomization (MR) analysis using the inverse variance weighted (IVW), weighted mode, weighted median and MR-Egger methods was performed. We used the publicly available summary statistics data sets of genome-wide association studies (GWAS) for H. pylori infection in individuals of European descent (case = 1,058, control = 3,625) as the exposure and a GWAS for non-cancer illness code self-reported: IBS (case = 10,939, control = 451,994) as the outcome.ResultsWe selected 10 single nucleotide polymorphisms at genome-wide significance from GWASs on H. pylori infection as the instrumental variables. The IVW, weighted mode, weighted median and MR-Egger methods all provided consistent evidence that suggests a lack of causal association between H. pylori and IBS. MR-Egger regression revealed that directional pleiotropy was unlikely to be biasing the result (intercept = −1e-04; P = 0.831). Cochran’s Q-test and the funnel plot indicated no evidence of heterogeneity and asymmetry, indicating no directional pleiotropy.ConclusionThe results of MR analysis support that H. pylori infection may not be causally associated with an increased risk of IBS.

While live commerce provides consumers with a new shopping experience, it also leads them to experience shopping failures and to develop a self-protection mechanism to prevent wrong purchases. To address this issue, merchants have attempted to explore new marketing methods for live commerce, giving rise to an offense and defense game between streamers and consumers. In this study, we sought to confirm the effectiveness of consumer protection mechanisms and the impact of streamers' information overload marketing strategy in live commerce. Accordingly, we constructed a hypothetical model based on protection motive theory and information overload theory. In addition, we analyzed the data from the simulated live streaming marketing on seven hundred people through partial least squares structural equation modeling. The results indicate that product utilitarian value uncertainty, consumers' experiential efficacy, and response costs, which are the main factors in the formation of consumer protection mechanisms, influence consumers' intention to stop their purchases. Streamers can circumvent consumer self-protection mechanisms through information overload marketing by reducing utilitarian value uncertainty and consumers' experiential efficacy and increasing consumers' response costs. However, consumers would be able to rebuild their self-protection mechanism through consumer resilience, which moderates the effects of information overload. This study's results provide important theoretical perspectives and new ideas for formulating marketing strategies for live commerce.

Recycling apparel and fabrics is essential for preserving resources and protecting the environment, providing considerable global advantages for ecology and society. This study sought to explore the participation of Chinese college students in the recycling of clothing and fabrics by combining the Theory of Planned Behavior (TPB), the Value-Belief-Norm theory (VBN), self-identity, school education, and perceived policy effectiveness to create a comprehensive model. A total of 1,027 valid samples were obtained through stratified sampling and random sampling, primarily sourced from Eastern China, and analyzed through Structural Equation Modeling (SEM) utilizing AMOS. The results of the research suggested the following: (1) College students’ biospheric values emerged as the most influential factor in predicting their inclination to participate in recycling behavior. (2) VBN (encompassing biospheric and altruistic values) and self-identity significantly contributed to shaping attitude and perceived behavioral control, which in turn impacted individuals’ intention to participate in recycling. (3) School education exerted a stronger moderating influence than perceived policy effectiveness on the relationship between attitude, perceived behavioral control, and intention. The comprehensive model proposed in this study demonstrated superior predictive capability in explaining college students’ willingness to participate in clothing and textiles recycling. It has been proven to be practical and effective. Lastly, schools should promote the practice of clothing and textiles recycling, cultivate good values, and utilize the power of social influence to encourage college students to participate in clothing and textiles recycling. The government should improve relevant laws and regulations, collaborate with academia, and adopt measures like incentives to create a pro-environment atmosphere.

Enhancing the alkalinity of the ocean is a promising approach for CO2 removal by promoting marine carbon sequestration. Olivine is a key candidate material for enhancing alkalinity owing to its release of silicates when dissolved in seawater. These released compounds serve as crucial nutrients for phytoplankton such as diatoms to foster their growth, which in turn accelerates olivine dissolution and further enhances carbon sequestration. In this study, we investigated the short-term synergistic CO2 removal effects of an olivine–diatom coculture system. Over a 6-day incubation period, the olivine dissolution was 92% to 144% higher in the olivine–diatom groups compared with the olivine-only groups. The olivine-only groups achieved a CO2 removal efficiency of 5.15% to 5.49%, while the olivine–diatom groups achieved a CO2 removal efficiency of 8.84% to 14.44%. Adding olivine was found to increase the total alkalinity by 70 to 100 μM and the diatom abundance by 26.4% to 58.4%. Diatom growth and the fixed carbon content were greatly enhanced, particularly during the later silicate-depleted stage when the Si:C ratio significantly exceeded that of groups without olivine. This mutually beneficial olivine–diatom coculture system offers a highly efficient CO2 removal strategy for addressing climate change. The results of this study contribute to our understanding of carbonate and biological carbon pump processes.

Abstract Balloon pulmonary angioplasty (BPA) has been proven effective for addressing technically inoperable chronic thromboembolic pulmonary hypertension (CTEPH). However, the effectiveness of BPA in technically operable CTEPH patients who, for various reasons, did not undergo the procedure remains an area requiring exploration. This study sought to assess the safety and efficacy of BPA in such cases. We collected and reviewed data from CTEPH patients who underwent BPA in a consecutive manner. Following multidisciplinary team (MDT) decisions, patients were classified into two groups: technically inoperable (group A) and operable (group B). Group B comprised patients deemed technically suitable for pulmonary endarterectomy (PEA) but who did not undergo the procedure for various reasons. All patients underwent a comprehensive diagnostic work‐up, including right heart categorization at baseline and the last intervention. This study compared changes in hemodynamic parameters, functional capacity, and quality of life between the two groups. In total, 161 patients underwent 414 procedures at our center, with Group A comprising 112 patients who underwent 282 BPA sessions and group B comprising 49 patients who underwent 132 BPA sessions. Significantly, both groups exhibited improvements in hemodynamics, functional capacity, and quality of life. The occurrence rate of complications, including hemoptysis and lung injury, was similar [12 (63.2%) vs. 7 (36.8%), p = 0.68]. BPA demonstrated favorable outcomes in patients with proximal CTEPH who did not undergo pulmonary endarterectomy. However, the clinical impact of BPA in technically operable CTEPH was found to be less significant than in inoperable cases.

Abstract Background Perihilar cholangiocarcinoma (pCCA) is a malignant tumor of the hepatobiliary system which is still associated with a challenging prognosis. Postoperative complications play a crucial role in determining the overall prognosis of patients with pCCA. Changes in body composition (BC) have been shown to impact the prognosis of various types of tumors. Therefore, our study aimed to investigate the correlation between BC, postoperative complications and oncological outcome in patients with pCCA. Methods All patients with pCCA who underwent curative‐intent surgery for pCCA between 2010 and 2022 were included in this analysis. BC was assessed using preoperative computed tomography and analyzed with the assistance of a 3D Slicer software. Univariate and multivariate binary logistic regression analyses were conducted to examine the relationship between BC and clinical characteristics including various measurements of postoperative complications and Cox regressions and Kaplan–Meier analysis to evaluate oncological risk factors in the study cohort. Results BC was frequently altered in patients undergoing curative‐intent liver resection for pCCA (n = 204) with 52.5% of the patients showing obesity, 55.9% sarcopenia, 21.6% sarcopenic obesity, 48.5% myosteatosis, and 69.1% visceral obesity. In multivariate analysis, severe postoperative complications (Clavien‐Dindo ≥3b) were associated with body mass index (BMI) (Odds ratio (OR) = 2.001, p = 0.024), sarcopenia (OR = 2.145, p = 0.034), and myosteatosis (OR = 2.097, p = 0.017) as independent predictors. Furthermore, sarcopenia was associated with reduced overall survival (OS) in pCCA patients (sarcopenia vs. no‐sarcopenia, 21 months vs. 32 months, p = 0.048 log rank). Conclusions BC is highly associated with severe postoperative complications in patients with pCCA and shows tendency to be associated impaired overall survival. Preoperative assessment of BC and interventions to improve BC might therefore be key to improve outcome in pCCA patients undergoing surgical therapy.

Natural products are a rich resource in drug discovery. In the report, series novel rutaecarpine-derived compounds with potent anti-inflammatory activity and therapeutic efficacy against dextran sulfate sodium (DSS)-induced ulcerative colitis (UC) were designed and synthesized. Thirty-two target compounds inhibiting on LPS-induced NO production in RAW264.7 cells were screened. Compound 7mA with the most potent inhibitory activity and low cytotoxicity was selected as representative compound for further studies on the anti-inflammatory efficacy and mechanism. The results indicated that 7mA could significantly inhibit the transcription or expression of iNOS, IL-6 and IL-1β via regulating the TLR4/MAPK/NF-κB signal pathway. What's more, 7mA also could alleviate UC in DSS-induced mice, and down-regulated the release of IL-6, IL-1β, inhibited activation of TLR4/MAPK/NF-κB pathway in mice model as well, suggesting that this new rutaecarpine-derived scaffold might serve as therapeutic candidate for further development to anti-inflammatory agent.

BackgroundWe attempted to develop a progression prediction model for local advanced rectal cancer(LARC) patients who received preoperative neoadjuvant chemoradiotherapy(NCRT) and operative treatment to identify high-risk patients in advance.MethodsData from 272 LARC patients who received NCRT and total mesorectal excision(TME) from 2011 to 2018 at the Fourth Hospital of Hebei Medical University were collected. Data from 161 patients with rectal cancer (each sample with one target variable (progression) and 145 characteristic variables) were included. One Hot Encoding was applied to numerically represent some characteristics. The K-Nearest Neighbor (KNN) filling method was used to determine the missing values, and SmoteTomek comprehensive sampling was used to solve the data imbalance. Eventually, data from 135 patients with 45 characteristic clinical variables were obtained. Random forest, decision tree, support vector machine (SVM), and XGBoost were used to predict whether patients with rectal cancer will exhibit progression. LASSO regression was used to further filter the variables and narrow down the list of variables using a Venn diagram. Eventually, the prediction model was constructed by multivariate logistic regression, and the performance of the model was confirmed in the validation set.ResultsEventually, data from 135 patients including 45 clinical characteristic variables were included in the study. Data were randomly divided in an 8:2 ratio into a data set and a validation set, respectively. Area Under Curve (AUC) values of 0.72 for the decision tree, 0.97 for the random forest, 0.89 for SVM, and 0.94 for XGBoost were obtained from the data set. Similar results were obtained from the validation set. Twenty-three variables were obtained from LASSO regression, and eight variables were obtained by considering the intersection of the variables obtained using the previous four machine learning methods. Furthermore, a multivariate logistic regression model was constructed using the data set; the ROC indicated its good performance. The ROC curve also verified the good predictive performance in the validation set.ConclusionsWe constructed a logistic regression model with good predictive performance, which allowed us to accurately predict whether patients who received NCRT and TME will exhibit disease progression.

Nanofluids have captured the attention of scientists due to their superior thermophysical properties compared to ordinary liquids. Consequently, nanofluids serve as suitable cooling agents applicable to systems requiring swift response to thermal changes, such as vehicle engines. The primary objective of this article is to delve into recent advancements in peristaltic pumping of nanofluids for engineering processes, particularly focusing on porous asymmetric channels. The article comprehensively discusses the influence of magnetic and incorporating temperature-dependent viscosity. Furthermore, the energy equation addresses thermal radiation and Joule heating effects, while considering velocity slip and convective boundary constraints. The nanomaterials play vital role in enhancing heat transfer characteristics, thereby offering control over the system's temperature. The temperature demonstrates a decreasing trend with an increase in the thermal radiation process.

The study of fluid flow and heat transport is found in many engineering applications such as boilers, nuclear plants, thermal energy storage, and underground pipelines. This study focuses on investigating the effects of isothermal source and sink on natural convection and entropy generation for Casson fluids using the finite element method. Under these considerations, fins ensure the effectiveness of heat transfer systems and flow patterns. Results describe that a higher Ra value leads to promote heat and mass transfer while Ha has the opposite impact. By increasing Ha value, results to retard convective heat transfer. As the Lewis number increases, so does the entropy due to deformation and the Bejan number. The shape optimization study about fins is performed in detail. The aspect ratio of cold fins is varied from 1.25 to 7, found that length and width are nearly directly related to entropy, mass, and heat transfer rates. The correlation coefficient for mean Nusselt and Sherwood number versus sink width is 0.9942, very close to 1, showing a very close direct relationship. The linear regression coefficients for mean Nusselt, Sherwood number and total entropy versus sink lengths are (0.7484, 2.2343), (0.7706, 2.254) and (2.4927, 5.8662), respectively.

The turbulent flow between concentric cylinders and its heat transfer performance is studied by the large eddy simulation. The models with longitudinal slit and helical slit spacing in the range from 168 to 672 mm on the outer cylinder are investigated to compare their heat transfer ability. Further, the notion of field synergy and entropy formation serves as the foundation for evaluating heat transfer qualities. According to the results, the enhancement effect of helical slits on heat transfer is better than that of longitudinal slits. Helical slits are more effective in promoting fluid mixing at different temperatures within the annulus. In terms of field synergy, the helical slit models exhibit a smaller field synergy angle compared to the longitudinal slit model at various Reynolds numbers from 3061 to 4592. Results of using helical slits indicate an improved coordination between the velocity and temperature fields. Thermodynamic analysis reveals that the helical slit models have lower entropy generation as compared to the longitudinal slit models. Higher efficiency in energy utilization and superior heat transfer properties of the helical slit models are noticed. Findings of this study provide valuable insights for the optimal design of various rotating machinery applications.

In this computational study, the tribological characteristics of the flow of a visco-plastic fluid around a pair of cylinders in a channel are thoroughly analyzed. To numerically solve the governing equations, this investigation makes use of the Galerkin's Finite Element Method (FEM) in conjunction with Newton's and PARDISO solvers. The stable finite element pair (P2/P1) has been selected for the space discretization purpose. The impacts of several physically important parameters on the flow characteristics are investigated in depth, including the spacing ratio (GP), the power law index (n), the Bingham number (Bn), and the Reynolds number (Re). When using different gap spacing ratios (GP), the drag coefficient (CD) and lift coefficient CL were found to be strongly dependent on GP. The pressure, velocity, and viscosity profiles are plotted for varying n and Bn. In addition, the velocity behavior is observed along y-direction in a channel through line graphs. Code validation is done as special case when Bn=0andn=1. It has been observed that the gap between the obstacles can influence the overall flow pattern and subsequently the drag and lift forces.