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Abstract Background Emerging evidence suggests that circadian rhythms play a role in the regulation of cardiovascular diseases (CVDs). We aim to examine the relationship between the 24-hour behavior rhythms (activity-rest and feeding-fasting rhythms) and stroke. Methods The study included 3201 adult participants with prediabetes/diabetes from the National Health and Nutrition Examination Survey (NHANES) 2011–2014. The 24-hour behavior rhythm indices were calculated using data from accelerometer wearable device and dietary recall for two nonconsecutive days. Six indices were calculated including interdaily stability (IS), intradaily variability (IV), relative amplitude (RA), average activity during the least active continuous 5-hour period (L5), Average activity during the most active continuous 10-hour period (M10) which reflects the activity-rest rhythm, and feeding rhythm score which reflects the feeding-fasting rhythm. These continuous variables were divided into quintiles for logistic regression models. Results Comparing participants in quintile 1, those in quintile 5 of IS and RA exhibited a lower odds of stroke. Conversely, participants in quintile 5 of IV, L5, and L5 start time demonstrated a higher odds of stroke. Furthermore, participants in quintile 5 of feeding rhythm score had a significantly lower odds of stroke. The associations of IV and feeding rhythm score with stroke were more pronounced in participants with diabetes compared to those with prediabetes/diabetes. No significant associations were observed between other 24-hour behavior rhythms and stroke. Conclusions Overall, this study highlights a significant association between 24-hour behavior rhythm and stroke in American adults with prediabetes/diabetes.

Abstract Determining rock mass mechanical parameters and accurately predicting tunnel deformation during tunnel construction remain challenging tasks. This study introduces a novel approach to calculate the Geological Strength Index by integrating indoor rock mechanics tests with geometric data from three-dimensional dense reconstruction. We utilized the Hoek-Brown strength criterion to develop a theoretical model for predicting tunnel deformation in fractured rock masses. Case studies reveal that the average value of Geological Strength Index for the Xiamen highway tunnel’s surrounding rock is 44. With support from the lining structure equivalent to 0.002–0.02 times the initial in-situ stress, the plastic zone thickness decreased by approximately 50%, and radial displacement was reduced by about 40%. Enhancing the lining structure’s support pressure significantly reduces the plastic zone radius and radial displacement. As the Geological Strength Index decreases, the nonlinearity between support pressure and plastic zone radius becomes more pronounced, with a similar trend observed for the relationship between support pressure and tunnel radial displacement. The relative deviation between predicted and measured values did not exceed 1.69%. The method accurately captures the effects of rock fragmentation and tunnel construction on plastic zone formation and displacement, offering an effective approach for the rapid and secure assessment of rock tunnel excavation stability using digital technology.

In the context of transitioning energy structures, thermal power generation is adapting to peak load regulation, highlighting the need for comprehensive studies on boiler combustion characteristics under varying load conditions. This study focuses on a 660 MW tangentially fired boiler, evaluating its combustion and pollutant generation at different operational loads: boiler maximum continuous rate (BMCR), turbine heat acceptance (THA), 75% of THA, and 40% of THA. The findings reveal a general decline in temperature, and nitrogen oxide concentration as the load decreases. However, at 40% THA, increased oxygen mole fractions lead to higher carbon dioxide and sulfur dioxide levels compared to other conditions. Through the Analytic Network Process, each parameter's impact is evaluated and scored to identify the most effective burner and deflection angle combinations. Optimal configurations are identified: a 10-degree rightward adjustment for ABDE layer burners at BMCR and a 10-degree leftward adjustment for BD layer burners at 40% THA, both enhancing combustion performance and reducing pollutants at the furnace outlet. For THA and 75% THA conditions, the industrial standard combination is recommended.

The lateral response of combined pile-raft foundations (CPRFs) adjacent to tunnel excavation is a challenging problem owing to the complexity of the pile-raft connections. In current engineering practices, the impact of these connections on the lateral performance of CPRFs is frequently overlooked, despite their importance. To address this issue, this study conducted three-dimensional finite element analyses to evaluate the contribution of pile-raft connections to the tunnelling-induced lateral performance of CPRFs in saturated clay. In the analysis, both passive and active loading at the pile head could be considered by varying the tunnel depth. Several parameter studies, such as relative pile-raft modulus, pile embedded modulus, pile embedded depths, and pile shaft skin friction, were conducted to determine the optimal design parameters for CPRFs. The results indicate that pile-raft connections significantly affect the tunnelling-induced deflections and bending moments of pile groups. Inspired by the results, a simplified design method, the pile-raft connection coefficient Kc was proposed. Additionally, the pile-head restraint percentage was established to make a relationship with the pile-raft connection coefficient in order to assess the pile-raft connection and guide the pile-raft design. In this paper, the recommended range value of Kc is 10–200 and the range value of pile-head restraint percentage is 24%–42%.

It has been found in the recent studies that the CO2 geological storage is one of the efficient methods to achieve a large amount of CO2 reduction, while the understanding of the transport law of CO2 in the rock pore space is fundamental to the flexibility of a safe and long-term CO2 geological storage scheme. The pore network model based on the core micro-structure reconstruction can not only reflect the real core pore and throat distribution law, but also reflect the distribution of pore space and its development characteristics, which is of importance in the field of multi-phase flow research in porous media. The Berea sandstone, which is more common in the reservoir, was selected to obtain two-dimensional CT images based on the micro-focus X-ray computed tomography (micro-CT) technology, and the digital images of core samples were reconstructed in ImageJ software through a series of image processing processes such as size cropping, noise reduction filtering and threshold segmentation, and binarized in the Matlab software via extraction functions. Then, via the maximum sphere algorithm, the pore-throat topological equivalent network in the experimental core samples was extracted through three main steps, including searching the maximum sphere, establishing the maximum sphere connectivity, identification of pores and throats and parameter calculation, and visualized by using Amira software to equate the pores and throats to a spherical rod models. By comparing the structural parameters of core porosity, coordination number, pore and throat geometry and shape factor obtained via different image processing and pore network extraction methods, a digital core reconstruction and pore network model extraction method that can better reflect the spatial characteristics of real core pores was determined, such as model 7: the mean value is set to 1.5 and median value is set to 2 during filtering. The Otsu algorithm was selected for threshold segmentation and the minimum aperture was set to 1 when the digital core was extracted by the maximum sphere method. The pore structure parameters of Berea core were measured as follows: the coordination number was distributed within 30 and the peak value was around 5. The pore radius was distributed within 80 μm and concentrated around 20 μm. The throat radius was distributed within 60 μm and concentrated around 10 μm. The pore shape factor and throat shape factor were distributed within 0.07, the peak of pore shape factor was around 0.03, and the peak of throat shape factor was around 0.035. Finally, based on the pore network two-phase seepage simulation program developed by Imperial College of Technology, the seepage simulation of CO2-replaced brine in porous media was carried out under the reservoir conditions of 50 ℃ and 12.4 MPa by characterizing brine with 0.103 mol/kg NaCl solution. Then, the capillary pressure curve and relative permeability curve during the drainage and imbibition cycle were analyzed in detail. The influence of the pore network extraction method on the multi-phase flow process in porous media was elucidated, and the reliability of the pore network modeling method and the accuracy of the obtained modeling parameters were demonstrated again.

[This corrects the article DOI: 10.1371/journal.pone.0258040.].

Abstract With the development of Internet technology, the problem of information overload has increasingly attracted attention. Nowadays, the recommendation system with excellent performance in information retrieval and filtering would be widely used in the business field. However, most existing recommendation systems are considered a static process, during which recommendations for internet users are often based on pre-trained models. A major disadvantage of these static models is that they are incapable of simulating the interaction process between users and their systems. Moreover, most of these models only consider users’ real-time interests while ignoring their long-term preferences. This paper addresses the abovementioned issues and proposes a new recommendation model, DRR-Max, based on deep reinforcement learning (DRL). In the proposed framework, this paper adopted a state generation module specially designed to obtain users’ long-term and short-term preferences from user profiles and user history score item information. Next, Actor-Critical algorithm is used to simulate the real-time recommendation process.Finally, this paper uses offline and online methods to train the model. In the online mode, the network parameters were dynamically updated to simulate the interaction between the system and users in a real recommendation environment. Experimental results on the two publicly available data sets were used to demonstrate the effectiveness of our proposed model.

The association between acrylamide (AA) and the development of cancer has been extensively discussed but the results remained controversial, especially in population studies. Large prospective epidemiological studies on the relationship of AA exposure with cancer mortality were still lacking. Therefore, we aimed to assess the association between AA biomarkers and cancer mortality in adult population from National Health and Nutrition Examination Survey (NHANES) 2003-2014. We followed 3717 participants for an average of 10.3 years. Cox regression models with multivariable adjustments were performed to determine the relationship of acrylamide hemoglobin adduct (HbAA) and glycidamide hemoglobin adduct (HbGA) with cancer mortality. Mediation analysis was conducted to demonstrate the mediated role of low-grade inflammation score (INFLA-score) in this correlation. Compared with the lowest quintile, participants with the highest quintile of HbAA, HbGA and HbAA+HbGA had increased cancer mortality risk, and the hazard ratios(HRs) were 2.07 (95%CI:1.04-4.14) for HbAA, 2.39 (95%CI:1.29-4.43) for HbGA and 2.48 (95%CI:1.28-4.80) for HbAA+HbGA, respectively. And there was a considerable non-linearity association between HbAA and cancer mortality (pfor non-linearity = 0.0139). We further found that increased INFLA-score significantly mediated 71.67% in the effect of HbGA exposure on increased cancer mortality risk. This study demonstrates that hemoglobin biomarkers of AA are positively associated with cancer mortality in adult American population and INFLA-score plays a mediated role in this process. Our findings can raise public awareness of environmental and dietary exposure to acrylamide and remind people to refrain from smoking or having acrylamide-rich foods.

BackgroundChrono-nutrition emphasized the importance of the intake time; however, less is known about the impact of dietary vitamin intake time on health. This study aimed to examine our hypothesis about which vitamin intake time could influence the natural course of cardiovascular disease (CVD).MethodsA total of 27,455 adults enrolled in the National Health and Nutrition Examination Survey (NHANES) during 2003–2014 were recruited. The 12 dietary vitamin intakes in the morning, afternoon, and evening were categorized into tertiles or quartiles. Cox-proportional hazard regression models were developed to evaluate the association of vitamin intake time with CVD and all-cause mortalities.ResultsCompared with participants in the lowest quartile, participants in the highest quartile of dietary VB2 intake in the morning had significantly lowest mortality risk of CVD [hazard ratio (HR)VB2 = 0.75, 95% CI: 0.60–0.94, p = 0.017]; whereas, participants in the highest quartile of dietary-vitamin B6 (VB6), vitamin C (VC), vitamin E (VE), and folate-equivalent consumed in the evening showed the lowest risks of CVD (HRVB6 = 0.77, 95% CI: 0.60–0.99, p = 0.103; HRVC = 0.80, 95% CI: 0.65–0.98, p = 0.050; HRVE = 0.75, 95% CI: 0.56–0.99, p = 0.032; HRfolate–equivalent = 0.78, 95% CI: 0.63–0.97, p = 0.116) and all-cause mortalities (HRVB6 = 0.81, 95% CI: 0.71–0.93, p = 0.006; HRVC = 0.85, 95% CI: 0.76–0.95, p = 0.004; HRVE = 0.84, 95% CI: 0.72–0.97, p = 0.011; HRfolate–equivalent = 0.80, 95% CI: 0.71–0.90, p = 0.001). Moreover, equivalently replacing 10% intake of dietary VB6, VC, VE, and folate-equivalent in the morning with evening were associated with 4% (HRVB6 = 0.96, 95% CI: 0.92–0.99), 5% (HRVC = 0.95, 95% CI: 0.92–0.99), 4% (HRVE = 0.96, 95% CI: 0.91–0.99), and 5% (HRfolate–equivalent = 0.95, 95% CI: 0.92–0.99) lower risk of CVD mortality.ConclusionThis study found that the optimal intake time of dietary VB2 was in the morning, and the optimal intake times of dietary VB6, VC, VE, and folate-equivalent were in the evening.

Objective: This study explored the effect of multiple-nutrient supplementation on muscle damage and liver and kidney function after vigorous exercise under heat.Methods: After an initial pilot trial comprising 89 male participants, 85 participants were recruited and assigned into three groups: a multiple-nutrient (M) group, a glucose (G) group, and a water (W) group. Multiple-nutrient supplements contain glucose, fructose, maltose, sodium, potassium, vitamin B1, vitamin B2, vitamin C, vitamin K, and taurine. Participants were organised to take a 3-km running test (wet-bulb globe temperature 32°C) after a short-term (7 days) supplement. Blood samples were obtained to detect biochemical parameters [glucose (GLU), aspartate aminotransferase (AST), alanine aminotransferase (ALT), blood urea nitrogen (BUN), uric acid (UA), creatinine (Cr), creatine kinase (CK), lactate dehydrogenase (LDH), and lactic acid], inflammation factors [interleukin-6 (IL-6) and tumour necrosis factor-α (TNF-α)], and oxidative stress biomarkers [superoxide dismutase (SOD) and 8-iso-prostaglandin F (2alpha) (8-iso-PGF2α)].Results: In the pilot trial, BUN decreased significantly in the M and G groups immediately after the running test. AST, Cr, and UA were significantly reduced 24 h after the running test with single-shot multiple-nutrient supplementation. In the short-term trial, multiple nutrients further prevented the elevation of CK (p = 0.045) and LDH (p = 0.033) levels 24 h after strenuous exercise. Moreover, we found that multiple nutrients significantly reduced IL-6 (p = 0.001) and TNF-α (p = 0.015) elevation immediately after exercise. Simultaneously, SOD elevation was significantly higher in the M group immediately after exercising than in the other two groups (p = 0.033). 8-iso-PGF2α was reduced in the M group 24 h after exercise (p = 0.036).Conclusions: This study found that multiple-nutrient supplementation promoted the recovery of muscle damage and decreased liver and kidney function caused by strenuous exercise in a hot environment, probably through the inhibition of secondary damage induced by increased inflammatory reactions and oxidative stress. In this respect, the current study has important implications for the strategy of nutritional support to accelerate recovery and potentially prevent heat-related illness. This study was prospectively registered on clinicaltrials.gov on June 21, 2019 (ID: ChiCTR1900023988).

Dibromoacetic acid (DBA) is a by-product of disinfection in drinking water, which could cause many adverse effects in test animals. However, little research on its neurotoxicity has been conducted, and its mechanism has not been elucidated. In the present study, ninety Sprague−Dawley rats were administered DBA at doses of 0, 30, and 90 mg/kg body weight for 28 days via oral gavage. We found that DBA could induce obvious neurotoxicity in the pineal gland as indicated by histological changes and impaired rhythm of melatonin in pineal and serum. In the mechanism study, transcriptome data showed that DBA exposure could induce 732 differential expression genes. Besides, GO and KEGG analysis results indicated that these genes were enriched in circadian rhythms, among which CREB1 had the most significant fold change. And immunofluorescence staining (IF) and immunohistochemical staining (IHC) results showed that the number of amber-colored masculine neurons for the p-CREB1 in the 90 mg/kg group was markedly lower, and staining for the p-CREB1 was weaker. Moreover, the results of PCR and western blot showed that DBA exposure could down-regulate the expressions of CREB1 and p-CREB1, leading to the decreased expressions of gene and protein of arylalkylamine N-acetyltransferase (AANAT), and then resulting in the impaired melatonin synthesis in the pineal and serum. In conclusion, DBA exposure is associated with abnormal melatonin rhythm via inhibition of the p-CREB1-AANAT signalling pathway.

Many wearables allow physiological data acquisition in sleep and enable clinicians to assess sleep outside of sleep labs. Belun Sleep Platform (BSP) is a novel neural network-based home sleep apnea testing system utilizing a wearable ring device to detect obstructive sleep apnea (OSA). The objective of the study is to assess the performance of BSP for the evaluation of OSA. Subjects who take heart rate-affecting medications and those with non-arrhythmic comorbidities were included in this cohort. Polysomnography (PSG) studies were performed simultaneously with the Belun Ring in individuals who were referred to the sleep lab for an overnight sleep study. The sleep studies were manually scored using the American Academy of Sleep Medicine Scoring Manual (version 2.4) with 4% desaturation hypopnea criteria. A total of 78 subjects were recruited. Of these, 45% had AHI < 5; 18% had AHI 5-15; 19% had AHI 15-30; 18% had AHI ≥ 30. The Belun apnea-hypopnea index (bAHI) correlated well with the PSG-AHI (r = 0.888, P < 0.001). The Belun total sleep time (bTST) and PSG-TST had a high correlation coefficient (r = 0.967, P < 0.001). The accuracy, sensitivity, specificity in categorizing AHI ≥ 15 were 0.808 [95% CI, 0.703-0.888], 0.931 [95% CI, 0.772-0.992], and 0.735 [95% CI, 0.589-0.850], respectively. The use of beta-blocker/calcium-receptor antagonist and the presence of comorbidities did not negatively affect the sensitivity and specificity of BSP in predicting OSA. A diagnostic algorithm combining STOP-Bang cutoff of 5 and bAHI cutoff of 15 events/h demonstrated an accuracy, sensitivity, specificity of 0.938 [95% CI, 0.828-0.987], 0.944 [95% CI, 0.727-0.999], and 0.933 [95% CI, 0.779-0.992], respectively, for the diagnosis of moderate to severe OSA. BSP is a promising testing tool for OSA assessment and can potentially be incorporated into clinical practices for the identification of OSA. Trial registration: ClinicalTrial.org NCT03997916 https://clinicaltrials.gov/ct2/show/NCT03997916?term=belun+ring&draw=2&rank=1.

In the existing research studies of hydraulic conductivity, most of them assume that soil consists of spheroidal particles and the value of hydraulic conductivity can be designated by the particle size. In the actual soil layers, the shape of soil particles is mostly ellipsoid or rod-like rather than ideal sphere. Therefore, the prediction of soil permeability using current method often deviates from the actual situation and cannot capture the anisotropy nature of soil without consideration of the effect of the axis size of soil particles in two different directions. To solve this problem, a new theoretical model with three different soil particle arrangements is introduced to derive a new hydraulic conductivity-particle size relationship considering the size difference in two directions. This model, from a microscopic perspective, divides pores into numerous pore units and obtains hydraulic conductivity of each tube unit, eventually predicting the permeability of soil layer based on an equivalence principle. The proposed equation is validated in comparison with experimental data from the existing literature and is proved to have a satisfied accuracy to predict hydraulic conductivity for a wide range of soils, from bentonite-silt mixed soils to sandy soils. The proposed model provides a new perspective for accurately predicting the hydraulic conductivity.

Abstract Understanding tumor cell heterogeneity and plasticity is crucial for overcoming drug resistance. Single-cell technologies enable analyzing cell states at a given condition, but catenating static cell snapshots to characterize dynamic drug responses remains challenging. Here, we propose scStateDynamics, an algorithm to infer tumor cell state dynamics and identify common drug effects by modeling single-cell level gene expression changes. Its reliability is validated on both simulated and lineage tracing data. Application to real tumor drug treatment datasets identifies more subtle cell subclusters with different drug responses beyond static transcriptome similarity and disentangles drug action mechanisms from the cell-level expression changes.

Recommending personalized content from massive data for users is the key function of the recommendation system. The recommendation process of the traditional recommendation systems is often regarded as static, which cannot reflect the changes of user's real-time interest. This paper addressed this problem and presented a recommendation model that leverages the ability of deep learning methods to effectively deal with decision-making problems. In this model, a state generation module containing gate recurrent unit (GRU) and attention network was designed to obtain user's long and short-term preferences as well as history scores. Then, an actor-critic algorithm was employed to imitate the real-time recommendations. We trained the proposed model and evaluated it on four wellknown public datasets. It is proved that the proposed model is superior to existing recommendation models. [ABSTRACT FROM AUTHOR]

Background This study examined the improvement of dysmenorrhoea and menorrhagia after uterine artery embolisation (UAE) in women with symptomatic adenomyosis and identified factors that could predict the improvement of dysmenorrhoea and menorrhagia.Methods This retrospective study included women with adenomyosis who underwent bilateral UAE between December 2014 and December 2016. The percentage of the volume of the absence of contrast enhancement on T1-weighted images was evaluated 5–7 days after UAE. A receiver operating characteristic (ROC) analysis was used to determine a cut-off point and predict the improvement of dysmenorrhoea and menorrhagia.Results Forty-eight patients were included. At 24 and 36 months after UAE, the improvement rates for dysmenorrhoea and menorrhagia were 60.4% (29/48) and 85.7% (30/35), and the recurrence rates were 19.4% (7/36) and 9.1% (3/33), respectively. Only the percentage of the volume of the absence of contrast enhancement on T1-weighted images was associated with the improvement of dysmenorrhoea (p = 0.001, OR = 1.051; 95% CI: 1.02–1.08) and menorrhagia (p = 0.006, OR = 1.077; 95% CI: 1.021–1.136). When the cut-off value of the ROC analysis was 73.1%, sensitivity, specificity, positive predictive value, and negative predictive value for the improvement of dysmenorrhoea were 58.6%, 94.7%, 94.4%, and 60%, while they were 58.9%, 80%, 100%, 100%, and 45.5% for the improvement of dysmenorrhoea.Conclusion Bilateral UAE for symptomatic adenomyosis led to good improvement of dysmenorrhoea and menorrhagia. The percentage of the volume of the absence of contrast enhancement on T1-weighted images of the uterus in postoperative magnetic resonance imaging might be associated with the improvement of dysmenorrhoea and menorrhagia.

Arsenic, a widespread toxic metalloid in groundwater, derives both from natural geological environment and industrial discharge, is extensively detected to be coexisting with organic contaminants, such as 2,4,6-trichlorophenol (TCP), a prior concerned pollutant. During biological remediation of groundwater, arsenic potentially intervenes microbial behaviors. This study found an opposite interference of arsenic in its two different valences (III and V) on the degradation of TCP by the functional bacteria, Sphingomonas fennica K101. As(III) inhibited TCP degradation in a concentration-dependent manner (from 0.1-10 mg/L), with a maximum inhibition rate of 35.5%, whereas As(V) exhibited promoting effects by 13.8% and 33.2% at 1 mg/L and 10 mg/L, respectively. Employing field emission transmission electron microscopy, quantum chemical calculations, fourier-transform ion cyclotron resonance mass spectrometry and metabolomic analysis, we unveil distinct interactions between cell membranes and arsenic in two valence states. Exposure to As(III) led to significant accumulation of As(III) in the cytoplasm, followed by interaction with intracellular ferritin (ferritin heavy chain 1), releasing iron ions and generating ROS. Subsequently, it induced ferroptosis and disrupted bacterial basal metabolism, thereby inhibiting TCP biodegradation. Oppositely, As(V) bound to a critical component sphingosine and triggered sphingosine polymerization, increasing membrane permeability, which was evidenced by measuring lactate dehydrogenase release. This process facilitated TCP transmembrane permeation by reducing membrane or extracellular secretion resistance. As(V) concurrently upregulated energy metabolism and accelerated TCP degradation. Our study elucidates the influence of prevalent arsenic on biodegradation efficacy, particularly amidst changing redox conditions associated with varying arsenic valences.

Pancreatic cancer is one of the most aggressive malignancies in the digestive system, characterized by vague early symptoms and rapid disease progression. Currently, treatment options for pancreatic cancer are limited, with unsatisfactory outcomes and poor prognosis, as the overall 5-year survival rate is less than 10%. Therefore, it is crucial to identify new biomarkers for pancreatic cancer.We analyzed the differential expression of EFNA5 at the mRNA level using data from the TCGA, GTEX, and GEO databases, followed by validation of EFNA5 protein expression differences through immunohistochemistry. Kaplan-Meier survival analysis and Cox regression analysis were used to explore the prognostic value of EFNA5. KEGG, GO enrichment analyses, and GSEA were employed to predict the biological functions of EFNA5. Bioinformatics algorithms were utilized to analyze the impact of EFNA5 on drug sensitivity, immune cell infiltration, and tumor mutational burden. Finally, we conducted cell phenotype experiments to investigate the effects of EFNA5 on the proliferation, migration, and invasion of pancreatic cancer cells. Bioinformatics data showed that the mRNA level of EFNA5 was higher in pancreatic cancer tissues compared to normal tissues. Immunohistochemistry experiments confirmed that the protein expression level of EFNA5 was significantly higher in pancreatic cancer tissues (n = 19) than in adjacent normal tissues (n = 19). Survival analysis indicated that the overall survival (OS) and progression-free survival (PFS) were worse in the high EFNA5 expression group compared to the low expression group. Univariate and multivariate Cox regression analyses demonstrated that EFNA5 is a risk factor affecting the prognosis of pancreatic cancer patients. KEGG pathway enrichment analysis revealed that differentially expressed genes (DEGs) between high and low EFNA5 expression groups were primarily enriched in pathways such as PI3K/Akt, axon guidance, and focal adhesion. GO enrichment analysis showed that DEGs were mainly associated with functions like epidermis development, cell adhesion, and intercellular junctions. Immune cell infiltration analysis found that EFNA5 expression was correlated with the infiltration levels of various immune cells. The tumor mutational burden was higher in the high EFNA5 expression group compared to the low expression group. Drug sensitivity analysis indicated that the high EFNA5 expression group had lower sensitivity to several commonly used chemotherapy drugs for pancreatic cancer. Cellular experiments demonstrated that knocking down EFNA5 inhibited the proliferation, invasion, and migration of pancreatic cancer cells. EFNA5 is overexpressed in pancreatic cancer tissues, and its high expression is associated with poor prognosis in pancreatic cancer patients. Downregulation of EFNA5 reduces the proliferation, migration, and invasion capabilities of the pancreatic cancer cell line BxPC-3. EFNA5 is closely related to the occurrence, development, prognosis, immune infiltration, and drug sensitivity of pancreatic cancer. Our study suggests that EFNA5 is a potential biomarker and therapeutic target.

Abstract Aims Surveys and research on the applications of the hepatic venous pressure gradient (HVPG) are important for understanding the current status and future development of this technology in China. This article aimed to investigate the status of hepatic venous pressure gradient measurement in China in 2022. Methods We investigated the overall status of HVPG technology in China—including hospital distribution, hospital level, annual number of cases, catheters used, average cost, indications, and current challenges by using online questionnaire. By counting the number and percentages of cases of these results, we hope to clarify the current status of HVPG measurements in China. Results According to the survey, 85 hospitals in China used HVPG technology in 2022 distributed across 29 provinces. A total of 4989 HVPG measurements were performed in all of the surveyed hospitals in 2022, of which 2813 cases (56.4%) were measured alone. The average cost of HVPG measurement was 5646.8 ± 2327.9 CNY. Of the clinical teams who performed the measurements (sometimes multiple per hospital), 94.3% (82/87) used the balloon method, and the majority of the teams (72.4%, 63/87) used embolectomy catheters. Conclusions This survey clarified the clinical application status of HVPG in China and confirmed that some medical institutions in China have established a foundation for this technology. It is still necessary to continue promoting and popularizing this technology in the future.

Abstract A pressing challenge in spatially resolved transcriptomics (SRT) is to benchmark the computational methods. A widely-used approach involves utilizing simulated data. However, biases exist in terms of the currently available simulated SRT data, which seriously affects the accuracy of method evaluation and validation. Herein, we present scCube ( https://github.com/ZJUFanLab/scCube ), a Python package for independent, reproducible, and technology-diverse simulation of SRT data. scCube not only enables the preservation of spatial expression patterns of genes in reference-based simulations, but also generates simulated data with different spatial variability (covering the spatial pattern type, the resolution, the spot arrangement, the targeted gene type, and the tissue slice dimension, etc.) in reference-free simulations. We comprehensively benchmark scCube with existing single-cell or SRT simulators, and demonstrate the utility of scCube in benchmarking spot deconvolution, gene imputation, and resolution enhancement methods in detail through three applications.

School bus routing problem (SBRP) has been studied for decades. Many successful approaches based on heuristics or metaheuristics have been developed for various SBRP problems. However, developing an effective algorithm for SBRP is still a very challenging task. This paper developed a Q-learning-based selection hyper-heuristic to solve basic and open single-school SBRP problems, which both aim to minimize the total travel distance. The proposed algorithm took a Qlearning algorithm as the high-level strategy to select a lowlevel heuristic from a set of low-level heuristics, which are dependent on the problem domain. The selected low-level heuristic was regarded as an action and then executed to improve the current solution. In each stage of the optimization process, the best action with the best cumulative rewards will be chosen to get better results. The presented algorithm was implemented and some experiments were carried out on some Capacitated vehicle routing problem (CVRP) instances and SBRP benchmark instances. Experiment results on two types of instances demonstrate that our proposed hyper-heuristic algorithm is more competition than existing approaches. [ABSTRACT FROM AUTHOR]

BackgroundIntermediate-stage (BCLC-B) hepatocellular carcinoma (HCC) beyond the up-to-11 criteria represent a significant therapeutic challenge due to high and heterogeneous tumor burden. This study evaluated the effectiveness and safety of transarterial chemoembolization (TACE) in combination with lenvatinib and tislelizumab for these patients.MethodsIn this retrospective cohort study, patients with unresectable intermediate-stage HCC beyond the up-to-11 criteria were enrolled and divided into TACE monotherapy (T), TACE combined with lenvatinib (TL), or TACE plus lenvatinib and tislelizumab (TLT) group based on the first-line treatment, respectively. The primary endpoint was overall survival (OS). The secondary outcomes included progression-free survival (PFS), tumor response according to RESIST1.1 and modified RECIST, and adverse events (AEs).ResultsThere were 38, 45, and 66 patients in the T, TL, and TLT groups, respectively. The TLT group exhibited significantly higher ORR and DCR than the other two groups, as assessed by either mRECIST or RECIST 1.1 (all P