Search

Pharmacotranscriptomic profiles, which capture drug-induced changes in gene expression, offer vast potential for computational drug discovery and are widely used in modern medicine. However, current computational approaches neglected the associations within gene‒gene functional networks and unrevealed the systematic relationship between drug efficacy and the reversal effect. Here, we developed a new genome-scale functional module (GSFM) transformation framework to quantitatively evaluate drug efficacy for in silico drug discovery. GSFM employs four biologically interpretable quantifiers: GSFM_Up, GSFM_Down, GSFM_ssGSEA, and GSFM_TF to comprehensively evaluate the multi-dimension activities of each functional module (FM) at gene-level, pathway-level, and transcriptional regulatory network-level. Through a data transformation strategy, GSFM effectively converts noisy and potentially unreliable gene expression data into a more dependable FM active matrix, significantly outperforming other methods in terms of both robustness and accuracy. Besides, we found a positive correlation between RSGSFM and drug efficacy, suggesting that RSGSFM could serve as representative measure of drug efficacy. Furthermore, we identified WYE-354, perhexiline, and NTNCB as candidate therapeutic agents for the treatment of breast-invasive carcinoma, lung adenocarcinoma, and castration-resistant prostate cancer, respectively. The results from in vitro and in vivo experiments have validated that all identified compounds exhibit potent anti-tumor effects, providing proof-of-concept for our computational approach.

Abstract Background In recent years, the association between systemic immune-inflammation index (SII) and the prognosis of patients with colorectal cancer (CRC) has remained a topic of considerable debate. To address this, the present study was carried out to investigate the prognostic significance of SII in CRC. Methods Databases including PubMed, Embase, the Cochrane Central Register of Controlled Trials (CENTRAL), and Web of Science were scrutinized up to March 27, 2024. The relationship between pre- and post-treatment SII levels and the prognosis of CRC was evaluated. Following literature screening, quality assessment, and extraction of outcome measures, a meta-analysis was conducted using Stata. Publication bias was assessed by funnel plots and Egger’s test. Results A total of 27 studies were included in the analysis. Pooled results demonstrated that a high SII level was associated with poor overall survival (OS, HR = 1.78, 95% CI = 1.40–2.26), progression-free survival (PFS, HR = 1.80, 95% CI = 1.26–2.56), disease-free survival (DFS, HR = 1.91, 95% CI = 1.43–2.56), and recurrence-free survival (RFS, HR = 3.29, 95% CI = 1.58–6.88). Notably, the association between pre-treatment SII and OS, PFS, and DFS was stronger than that observed for post-treatment SII, indicating that treatment may attenuate the predictive valueof SII for survival outcomes. Additionally, elevated SII was correlated with poor tumor differentiation, tumor location in the rectum, and larger tumor size ≥ 5 cm. Conclusion Our meta-analysis suggested that a high SII is a predictor of poor prognosis in CRC patients. High SII levels were strongly correlated with inferior OS, PFS, DFS, and RFS. The relationship between SII and survival outcomes was attenuated post-treatment compared to pre-treatment. Additionally, elevated SII was correlated with clinicopathological factors in CRC patients. These findings suggest that SII can serve as an independent prognostic indicator for CRC.

The status quo of low sustainability of urban landscape symbiosis design programme and low referability of the corresponding comprehensive evaluation method, the study will take the environmental and ecological value as the symbiosis goal to design the urban landscape. The study constructs a comprehensive evaluation model of industrial heritage urban landscape ecology, researches each index affecting landscape ecology, and determines the weight of each influence index by combining qualitative and quantitative methods. The maximum influence factors of the four criteria layers of emotion, culture, material and ecology are pleasure, obvious cultural symbols, appropriate scale and microclimate regulation, and the corresponding values are 0.313, 0.404, 0.315 and 0.495, respectively. Compared with that before the introduction of the self-organised neural network fusion K-Means clustering algorithm, the ecological evaluation scores of the urban landscape of the industrial heritage are much closer to the real situation, and the overall error is much higher. The ecological evaluation model of industrial heritage buildings is closer to the real situation, and the overall error fluctuation is 0.012–0.020. The precision-recall curve of the comprehensive evaluation model of industrial heritage buildings is more advantageous than that of other comprehensive evaluation models. The results of the study provide a scientific reference basis for the design of the external landscape environment of industrial heritage buildings, and provide a strong scientific support for the ecological symbiosis between old industrial buildings and the environment under the concept of sustainability.

Abstract Reduced muscle mass has been associated with the progression and prognosis of amyotrophic lateral sclerosis (ALS). However, it remains unclear whether decreased muscle mass is a risk factor for ALS or a consequence of motor neuron degeneration. Recently, serum creatinine-to-cystatin C ratio (CCR) have emerged as promising biomarkers for assessing muscle mass. We aimed to explore the association between CCR and the incidence of ALS using data from the UK Biobank. Between 2006 and 2010, 446,945 participants were included in the baseline. CCR was calculated as the ratio of serum creatinine to cystatin C. Cox regression models were used to analyze the relationship between CCR and ALS incidence. Furthermore, subgroup analyses were conducted to investigate potential covariates in these relationships. After adjusting for all covariates, the multivariate Cox regression analysis revealed a significant association between decreased CCR and an increased risk of ALS (hazard ratio (HR) = 0.990, 95% confidence interval (CI): 0.982–0.999, P = 0.026). Participants were stratified into groups based on CCR tertiles. Compared with participants in the highest tertiles of CCR, those in the lowest (HR = 1.388, 95% CI: 1.032–1.866, P = 0.030) and medium tertiles (HR = 1.348, 95% CI: 1.045–1.739, P = 0.021) had an increased risk of ALS incidence. Subgroup analysis showed that the relationship between CCR and ALS incidence was particularly significant among participants aged

Abstract Opioid use disorder (OUD) has been linked to macroscopic structural alterations in the brain. The monthly injectable, extended-release formulation of μ-opioid antagonist naltrexone (XR-NTX) is highly effective in reducing opioid craving and preventing opioid relapse. Here, we investigated the neuroanatomical effects of XR-NTX by examining changes in cortical thickness during treatment for OUD. Forty-seven OUD patients underwent structural magnetic resonance imaging and subjectively rated their opioid craving ≤1 day before (pre-treatment) and 11 ± 3 days after (on-treatment) the first XR-NTX injection. A sample of fifty-six non-OUD individuals completed a single imaging session and served as the comparison group. A publicly available [¹¹C]carfentanil positron emission tomography dataset was used to assess the relationship between changes in cortical thickness and μ-opioid receptor (MOR) binding potential across brain regions. We found that the thickness of the medial prefrontal and anterior cingulate cortices (mPFC/aCC; regions with high MOR binding potential) was comparable between the non-OUD individuals and the OUD patients at pre-treatment. However, among the OUD patients, mPFC/aCC thickness significantly decreased from pre-treatment to on-treatment. A greater reduction in mPFC/aCC thickness was associated with a greater reduction in opioid craving. Taken together, our study suggests XR-NTX-induced cortical thickness reduction in the mPFC/aCC regions in OUD patients. The reduction in thickness does not appear to indicate a restoration to the non-OUD level but rather reflects XR-NTX’s distinct therapeutic impact on an MOR-rich brain structure. Our findings highlight the neuroplastic effects of XR-NTX that may inform the development of novel OUD interventions.

Conclusion: The perimenopausal period acts as a potential factor in introducing insulin resistance as evidenced by impaired insulin action and altered expression profiles of exosomal miRNAs and hepatic genes. The present study contributes to the understanding that abnormal cargos carried by plasma exosomes, such as miRNAs, may be related to altered expression of the corresponding genes in the liver and abnormal insulin response.

Radix Pueraria lobata has been recognized as a medicine and functional food, whose polysaccharide is its main bioactive component. In this study, we employed the response surface method to optimize the extraction of a polysaccharide from Radix Puerariae lobatae (PLP). Based on a single-factor experiment, three levels of liquid–material ratio, extraction time, and extraction temperature were selected for the response surface experiment. We established a quadratic regression equation of the extraction rate. The optimal combination conditions were obtained through regression analysis and ridge analysis. The optimal extraction yield of PLP was up to 5.526%, which was not significantly different from the verified value. Biologically, PLP1, a homogeneous P. lobatae polysaccharide isolated and purified from PLP, exhibited significant antioxidant and hypoglycemic properties in vitro. These findings provide an important foundation for the development and utilization of P. lobatae resources.

Background/Aims: Metabolic-associated fatty liver disease (MAFLD) is a common cause of chronic liver disease worldwide. However, there is currently no recognized effective drugs for treating it. Materials and Methods: In this study, we investigated the efficacy of Honokiol (HNK) in vitro for mitigating MAFLD. Then, 0.4 mM palmitic acid (PA) and LO2 cells were used to establish the MAFLD model. The protective effect of HNK on MAFLD was confirmed by Oil Red O staining and cell counting kit (CCK-8) assay in LO2 cell line. Quantitative real-time polymerase chain reaction (qRT-PCR) and Western blot were carried out to analyze the regulatory role of HNK on Nrf2 and RIPK3 signaling pathways. The effect of HNK and its downstream signaling pathways on oxidative stress were verified by the detection of reactive oxygen species (ROS), malondialdehyde (MDA), catalase (CAT), and superoxide dismutase (SOD). The concentration of IL-1β, IL-6L, and TNF-α was assessed by enzyme-linked immunosorbent assay (ELISA). Results: The middle concentration of HNK (50 μmol/L) was selected as the best option for inhibiting lipidosis and oxidative stress in MAFLD models. Honokiol mitigates MAFLD via activation of nuclear factor E2-related factor 2 (Nrf2) signaling pathways in vitro. Honokiol suppressed MAFLD via activating the Nrf2 signaling pathway to play an antioxidant and anti-inflammatory role. Also, HNK regulates Nrf2 and RIPK3 signaling pathways to mitigate MAFLD. Conclusion: Our results showed that HNK may suppress the oxidative stress and inflammation in MAFLD via activation of Nrf2 signaling pathway.

Objective: To explore a precise association between tumor location and lymph node (LN) biopsy algorithm in uterine confined endometrial cancer (EC). Materials and methods: Patients with EC treated in the Department of Obstetrics and Gynecology, South Branch of Fujian Provincial Hospital were included in this observational retrospective study. Based on the procedure of treatment, patients were separated to stage I (2015.07–2019.09) and stage II (2019.09–2021.9). In each stage, patients were separated to high and low-risk group by the predicted results. Patients in the high-risk group received systematic lymphadenectomy in stage I and sentinel lymph node (SLN) dissection in stage II. The efficiency of lymph node metastasis (LNM) detection rates was compared between stage I and stage II cases. Precise lymph node biopsy algorithm was also constructed based on the outcomes of stage II. Results: Overall, 43 patients, 28 in stage I and 15 in stage II, were included in the study. No recurrence or death cases had been found within follow-up terms. Based on the difference in the detection efficiency of LNM (p > 0.05), there was no difference between two stages. Thus, systematic lymphadenectomy and SLN biopsy provided similar success rates. The location of tumor site was also important for deciding whether pelvic or para-aortic SLN should be sampled for LNM. Conclusions: Precise SLN biopsy for EC confined to the uterus showed comparable LNM detection rate as systematic lymphadenectomy. EC location may be used to determine whether pelvic or para-aortic SLN sampling should be conducted for treatment.

Background: The occurrence of sleep disturbances in amyotrophic lateral sclerosis (ALS) patients is widely reported. However, there is still a lack of reliable evidence of a relationship between sleep disturbances and the risk of developing ALS. The aim of this study was to prospectively investigate the longitudinal associations between sleep traits and the risk of incident ALS. Methods: We included information from 409,045 individuals from the prospective cohort of the UK Biobank. Sleep traits at baseline were measured using a standardized questionnaire. All sleep traits were analyzed in relation to the subsequent incidence of ALS using Cox proportional hazards models. Results: Multivariate analysis showed that 6–7 h of sleep was related to the lowest risk for ALS. A long sleep duration (≥8 h) was associated with an increased risk of ALS incidence (HR: 1.31, 95% CI: 1.07–1.61; p = 0.009). A short sleep duration (p = 0.021) in females. In participants aged ≥65 years, eveningness was associated with increased ALS risk (HR: 1.32, 95% CI: 1.08–1.61; p = 0.006). Conclusion: Our results hint at a sleep duration that is too short or too long, and certain chronotypes might be related to the risk of developing ALS. Despite the limitations imposed by the study design and the subjectivity of sleep information, our findings suggest that sleep disturbances may influence the risk of developing ALS.

With the rapid global growth in demand for renewable energy, the traditional energy structure is accelerating its transition to low-carbon, clean energy. Lithium-ion batteries, due to their high energy density, long cycle life, and high efficiency, have become a core technology driving this transformation. In lithium-ion battery energy storage systems, precise state estimation, such as state of charge, state of health, and state of power, is crucial for ensuring system safety, extending battery lifespan, and improving energy efficiency. Although physics-based state estimation techniques have matured, challenges remain regarding accuracy and robustness in complex environments. With the advancement of hardware computational capabilities, data-driven algorithms are increasingly applied in battery management, and multi-model fusion approaches have emerged as a research hotspot. This paper reviews the fusion application between physics-based and data-driven models in lithium-ion battery management, critically analyzes the advantages, limitations, and applicability of fusion models, and evaluates their effectiveness in improving state estimation accuracy and robustness. Furthermore, the paper discusses future directions for improvement in computational efficiency, model adaptability, and performance under complex operating conditions, aiming to provide theoretical support and practical guidance for developing lithium-ion battery management technologies.

Abstract The ionic transport process is an important counterpart to charge transport in oil‐paper insulation, and it significantly impacts oil flow electrification at the oil‐paper interface. Despite this, the dynamics of this phenomenon and the underlying mechanisms remain unclear, particularly at the molecular level. To understand this fundamental aspect, we conduct Molecular Dynamics study on the transport behaviour of an impurity ion in different oil‐paper insulation models under various external electric fields. Different influence factors, such as external electric fields, temperatures, and local structural characteristics, are investigated in relation to the corresponding ionic mobility in different polymer models. According to the simulations, ionic mobility and its response to electric fields are higher in weaker electrostatic models. As a result, mineral oil exhibits the highest ionic mobility and the most substantial enhancement of ionic mobility by external electric fields, followed by vegetable oil, oil‐paper blends, and insulating paper. This significant deviation in ionic mobility between oil and paper leads to the formation of an electric double layer near the oil‐paper interface. The underlying physical mechanisms of different ionic mobility and its response to the electric field in different polymer models could be explained by the different polymer structural influences in terms of interaction energy and coordination numbers in a static manner, as well as by the interactions between the impurity ion and its surrounding atoms in terms of lifetime correlation functions and velocity autocorrelation functions in a dynamic manner. In addition, the influence of temperature on ionic mobility in mineral and vegetable oil is examined, and their activation energies are calculated. Advancing in the fundamental understanding of the dynamics of the ion transport process in oil‐paper insulation is vital to improving their insulating properties for oil‐impregnated power transformers.

The solid waste and waste acid generated during the production of titanium dioxide contain considerable amount of scandium, which are valuable secondary resources. In this study, the titanium dioxide waste acid was used to leach the scandium-containing solid waste, and the leached solution was pretreated for iron removal by reduction-crystallization process. After that, scandium was recovered from the leached solution by using the P204-TBP co-extraction system. The process parameters were investigated systematically. The results showed that iron powder reduction-crystallization for iron removal at molar ratio of Fe:Fe3+ = 0.25 was most suitable for subsequent extraction, and the scandium extraction efficiency could reach 100% using 15% P204-5% TBP at 25 °C with A/O = 8. This study provided a novel process for treating scandium-bearing solid waste with scandium-bearing waste acid, showing great potential for industrial application.

Abstract Paeoniflorin (PF) is a natural plant ingredient with remarkable antitumor effects. Herein, we investigated the biological effects and mechanism of PF in colorectal cancer (CRC) cell stemness. The messenger RNA (mRNA) and protein expressions were assessed using quantitative real‐time polymerase chain reaction and western blot. The viability, proliferation, and migration and invasion of CRC cells were evaluated using cell counting kit‐8, clone‐formation, and transwell migration and invasion assays, respectively. The sphere‐formation capacity was determined using the sphere‐formation assay. A dual‐luciferase reporter gene assay was employed to analyze the interaction between miR‐3194‐5p and catenin beta‐interacting protein 1 (CTNNBIP1). The viability, migration, invasion, epithelial–mesenchymal transition, and stemness of CRC cells were repressed by PF. MiR‐3194‐5p was upregulated in CRC tissues and cells. MiR‐3194‐5p knockdown suppressed CRC cell stemness, while miR‐3194‐5p overexpression had the opposite effect. In addition, the inhibition of CRC cell stemness caused by PF was eliminated by miR‐3194‐5p overexpression. CTNNBIP1 functioned as the target of miR‐3194‐5p, whose knockdown abrogated the repression of CRC cell stemness and Wnt/β‐catenin signaling activation by PF.PF regulated the miR‐3194‐5p/CTNNBIP1/Wnt/β‐catenin axis to repress CRC cell stemness.

ObjectiveThe occurrence of immune-mediated diseases (IMDs) in amyotrophic lateral sclerosis (ALS) patients is widely reported. However, whether IMDs and ALS is a simple coexistence or if there exists causal relationships between the two has been a subject of great interest to researchers.MethodsA total of 454,444 participants from the prospective cohort of UK Biobank were recruited to investigate the longitudinal association between IMDs and ALS. Previously any IMDs and organ specific IMDs were analyzed in relation to the following incident ALS by Cox-proportional hazard models. Subgroup analyses were performed to explore the covariates of these relationships.ResultsAfter adjusting for potential covariates, the multivariate analysis showed that any IMDs were associated with an increased risk of ALS incidence (HR:1.42, 95%CI:1.03-1.94). IMDs of the endocrine-system and the intestinal-system were associated with increased risk of ALS incidence (endocrine-system IMDs: HR:3.01, 95%CI:1.49-6.06; intestinal system IMDs: HR:2.07, 95%CI: 1.14-3.77). Subgroup analyses revealed that immune burden, including IMD duration and the severity of inflammation had specific effects on the IMD-ALS association. In participants with IMD duration≥10 years or CRP≥1.3mg/L or females, previous IMDs increased the risk of incident ALS; however, in participants with IMD duration

There are abundant marine carbonate rock resources in China, which are dominated by fractured-vuggy carbonate oil and gas reservoirs accounting for over two thirds of proved reserves. The fractured-vuggy carbonate condensate gas reservoir in the Tarim Basin is at a burial depth of 4500–7000 m with the characteristics of extremely strong reservoir heterogeneity, complicated and diverse reservoir seepage media, complex fluid properties and quite difficult static characterization, which brings many challenges to reserve evaluation, development plan design and performance analysis. In order to improve the recovery factor of this type of oil and gas reservoir, this paper takes the dynamic characterization to supplement the static characterization and combines each other to improve the accuracy. In addition, based on many years' of dynamic and static research and development practice, the key enhanced gas recovery (EGR) technologies for fractured-vuggy carbonate condensate gas reservoirs are innovatively developed, such as the high-accuracy dynamic characterization technology with dynamic and static iteration for fractured-vuggy body in the strongly attenuated area of desert by taking seismic inversion information as the basis and 3D numerical well test as the core, the multi-target 3D development technology in one well to improve reserve production of fractured-vuggy condensate gas reservoirs, and the gas-lift depressurization EGR technology for fractured-vuggy condensate gas reservoirs. In conclusion, this technological system better solves the key difficulties in the fine characterization of fractured-vuggy body, reserve production improvement and abandonment pressure reduction of well. What's more, it realizes the fine reservoir characterization of fractured zones and feather-shaped fractured zones and the accurate prediction of key development indexes, and increases the deployment success rate of effective wells and efficient wells by 26% compared with that in the initial stage of large-scale productivity construction. To sum up, these technologies provide powerful technical support and reference experience for the scientific and efficient development of fractured-vuggy carbonate condensate gas reservoirs.

Abstract Previous studies have found that migraine patients are associated with white matter lesions (WMLs), but the causal relationship between the two remains unclear. We intend to explore the bidirectional causal relationship between migraine and WMLs using a two-sample mendelian randomization (MR) method. We employed summary-level data from a recent large-scale genome-wide association study (GWAS) that characterized three white matter (WM) phenotypes: white matter hyperintensities (WMH, N = 18,381), fractional anisotropy (FA, N = 17,673), and mean diffusivity (MD, N = 17,467), as well as migraine (N = 589,356). The inverse variance-weighted (IVW) method was used as the main approach for analyzing causality. Weighted median analysis, simple median analysis, and MR-Egger regression served as complementary methods. The bidirectional MR study affords no support for causality between WMLs and migraine. In all MR methods, there was no obvious causal evidence between them. In our bidirectional MR study, we didn't reach this conclusion that WMLs can cause migraine, migraine wouldn’t increase the risk of WMLs, either.

Aiming at the current bottleneck of constructing a fine geomagnetic fingerprint library that required a lot of labor costs, two generative models called the conditional variational autoencoder and the conditional confrontational generative network were proposed, which could collect a small number of data samples for a given location, and generate pseudo-label fingerprints.At the same time, in order to solve the problem of low positioning accuracy of single-point geomagnetic fingerprints, a geomagnetic sequence positioning algorithm based on attention mechanism of convolutional neural network-gated recurrent unit was designed, which could effectively use the spatial and temporal characteristics of fingerprints to achieve precise positioning.In addition, a real-time, portable mobile terminal data collection and positioning system was also designed and built.The actual test shows that the proposed model can effectively construct the available geomagnetic fingerprint database, and the average error of the proposed algorithm can reach 0.16 m.

Abstract This paper proposes a novel joint decision and estimation (JDE) solution for the multi-target detection and tracking (MDT) problem. MDT aims to jointly detect the number of targets and estimate their states, which is essentially a JDE problem since detection and tracking are highly coupled. Thus, a joint solution which can utilize the coupling is preferable. However, the existing JDE approach has either poor performance or excessive design parameters without considering the MDT problem realities, i.e., the losses that different decisions may lead to. Therefore, we propose a compact conditional JDE (CCJDE)-based MDT method with less design parameters but superior performance. Specifically, we propose a CCJDE-based MDT risk which unifies the detection and tracking risks in a compact way. Then, we derive the joint detection and tracking solution accounting for their couplings, where the joint probabilistic data association filter is adopted due to its advantageous performance and the adaptability to the JDE framework. Then, an efficient CCJDE-MDT algorithm is developed. Besides, some parameter designing guidelines are presented by considering the MDT realities. Simulation results verify the effectiveness of the proposed CCJDE-MDT method, which outperforms the traditional decision-then-estimation in joint performance and also beats the existing recursive joint decision and estimation(RJDE) method in many cases.

Outbreaks of infectious diseases pose significant threats to human life, and countries around the world need to implement more precise prevention and control measures to contain the spread of viruses. In this study, we propose a spatial-temporal diffusion model of infectious diseases under a discrete grid, based on the time series prediction of infectious diseases, to model the diffusion process of viruses in population. This model uses the estimated outbreak origin as the center of transmission, employing a tree-like structure of daily human travel to generalize the process of viral spread within the population. By incorporating diverse data, it simulates the congregation of people, thus quantifying the flow weights between grids for population movement. The model is validated with some Chinese cities with COVID-19 outbreaks, and the results show that the outbreak point estimation method could better estimate the virus transmission center of the epidemic. The estimated location of the outbreak point in Xi'an was only 0.965 km different from the actual one, and the results were more satisfactory. The spatiotemporal diffusion model for infectious diseases simulates daily newly infected areas, which effectively cover the actual patient infection zones on the same day. During the mid-stage of viral transmission, the coverage rate can increase to over 90%, compared to related research, this method has improved simulation accuracy by approximately 18%. This study can provide technical support for epidemic prevention and control, and assist decision-makers in developing more scientific and efficient epidemic prevention and control policies.

Abstract Background Awake prone positioning has been widely used in non-intubated patients with acute hypoxic respiratory failure (AHRF) due to COVID-19, but the evidence is mostly from observational studies and low-quality randomized controlled trials (RCTs), with conflicting results from published studies. A systematic review of published high-quality RCTs to resolve the controversy over the efficacy and safety of awake prone positioning in non-intubated patients with AHRF due to COVID-19. Methods Candidate studies were identified through searches of PubMed, Web of Science, Cochrane, Embase, Scopus databases from December 1, 2019 to November 1, 2022. Literature screening, data extraction and risk of bias assessment were independently conducted by two researchers. Results Eight RCTs involving 2657 patients were included. Meta-analysis of fixed effects models showed that awake prone positioning did not increase mortality(OR = 0.88, 95%CI [0.72, 1.08]), length of stay in ICU (WMD = 1.14, 95%CI [-0.45, 2.72]), total length of stay (WMD = 0.11, 95%CI [-1.02, 1.23]), or incidence of adverse events (OR = 1.02, 95%CI [0.79, 1.31]) compared with usual care, but significantly reduced the intubation rate (OR = 0.72, 95%CI [0.60, 0.86]). Similar results were found in a subgroup analysis of patients who received only high flow nasal cannula (Mortality: OR = 0.86, 95%CI [0.70, 1.05]; Intubation rate: OR = 0.69, 95%CI [0.58, 0.83]). All eight RCTs had high quality of evidence, which ensured the reliability of the meta-analysis results. Conclusions Awake prone positioning is safe and feasible in non-intubated patients with AHRF caused by COVID-19, and can significantly reduce the intubation rate. More studies are needed to explore standardized implementation strategies for the awake prone positioning. Trial registration CRD42023394113.

In practical oilfield production, the phenomenon of water influx typically shortens the water-free recovery period of wells, leading to water flooding and causing a sharp decline in the production well yields, bringing great harm to production. Water invasion usually occurs as a result of the elastic expansion of the water as well as the compaction of the aquifer pore space. However, it can be due to the special characteristics of fractured-vuggy reservoirs such as non-homogeneity and the discrete distribution of the pore spaces. It is challenging to use traditional seepage flow theories to analyze the characteristics of water influx. Also, reservoir numerical simulation methods require numerous parameters which are difficult to obtain, which significantly reduces the accuracy of the results. In this study, considering the driving energy for water influx, a water influx characteristic model was obtained by fitting a graph plate. Subsequently, an iterative calculation method was used to simultaneously obtain water influx volume and OOIP. The aquifer to hydrocarbon ratio was determined by fitting the water influx curve with the graphic plate. Results show that the calculation method is sensitive to the values of reservoir pressure and the crude oil formation volume factor. After applying the method to one field case, it was discovered that water influx performance can be characterized into two types, i.e., linear water influx and logarithmic water influx. In the early stages, the water influx rate of logarithmic water influx is greater compared to linear water influx. However, the volume and energy of waterbody are limited, and the water invasion phenomenon occurs almost exclusively within a short period after the invasion. On the other hand, the volume of waterbody invaded by linear water influx is larger, and it can maintain a stable rate of water influx. The results of the study can provide theoretical support for the waterbody energy evaluation and dynamic analysis of water influx, as well as the control and management of water in these types of reservoirs.

Abstract Objectives To explore an optimal model to predict the response of patients with axillary lymph node (ALN) positive breast cancer to neoadjuvant chemotherapy (NAC) with machine learning using clinical and ultrasound-based radiomic features. Methods In this study, 1014 patients with ALN-positive breast cancer confirmed by histological examination and received preoperative NAC in the Affiliated Hospital of Qingdao University (QUH) and Qingdao Municipal Hospital (QMH) were included. Finally, 444 participants from QUH were divided into the training cohort (n = 310) and validation cohort (n = 134) based on the date of ultrasound examination. 81 participants from QMH were used to evaluate the external generalizability of our prediction models. A total of 1032 radiomic features of each ALN ultrasound image were extracted and used to establish the prediction models. The clinical model, radiomics model, and radiomics nomogram with clinical factors (RNWCF) were built. The performance of the models was assessed with respect to discrimination and clinical usefulness. Results Although the radiomics model did not show better predictive efficacy than the clinical model, the RNWCF showed favorable predictive efficacy in the training cohort (AUC, 0.855; 95% CI 0.817–0.893), the validation cohort (AUC, 0.882; 95% CI 0.834–0.928), and the external test cohort (AUC, 0.858; 95% CI 0.782–0.921) compared with the clinical factor model and radiomics model. Conclusions The RNWCF, a noninvasive, preoperative prediction tool that incorporates a combination of clinical and radiomics features, showed favorable predictive efficacy for the response of node-positive breast cancer to NAC. Therefore, the RNWCF could serve as a potential noninvasive approach to assist personalized treatment strategies, guide ALN management, avoiding unnecessary ALND.

The point-feature label placement (PFLP) refers to the process of positioning labels near point features on a map while adhering to specific rules and guidelines, finally obtaining clear, aesthetically pleasing, and conflict-free maps. While various approaches have been suggested for automated point feature placement on maps, few studies have fully considered the spatial distribution characteristics and label correlations of point datasets, resulting in poor label quality in the process of solving the label placement of dense and complex point datasets. In this paper, we propose a point-feature label placement algorithm based on spatial data mining that analyzes the local spatial distribution characteristics and label correlations of point features. The algorithm quantifies the interference among point features by designing a label frequent pattern framework (LFPF) and constructs an ascending label ordering method based on the pattern to reduce interference. Besides, three classical metaheuristic algorithms (simulated annealing algorithm, genetic algorithm, and ant colony algorithm) are applied to the PFLP in combination with the framework to verify the validity of this framework. Additionally, a bit-based grid spatial index is proposed to reduce cache memory and consumption time in conflict detection. The performance of the experiments is tested with 4000, 10000, and 20000 points of POI data obtained randomly under various label densities. The results of these experiments showed that: (1) the proposed method outperformed both the original algorithm and recent literature, with label quality improvements ranging from 3 to 6.7 and from 0.1 to 2.6, respectively. (2) The label efficiency was improved by 58.2% compared with the traditional grid index.

The cretaceous gas reservoir in Kelasu Gas Field of the Tarim Basin is a rare ultra-deep and ultra-high pressure fractured tight sandstone gas reservoir where multi-scale discrete fractures of matrix, fracture and fault are developed, so its development cannot be conducted just based on static and dynamic reservoir description. In order to solve this problem, this paper establishes a numerical well test model of vertical wells based on matrix, fractures and faults (large fractures and small faults) by combining the random generation of natural fracture networks with the unstructured discrete fracture modeling method to break through the traditional continuous medium well test model. In addition, the model is solved by using the finite element method with mixed element, and the typical well test type curves under different random fracture networks are obtained. And the following research results are obtained. First, based on the observed data, the fracture network distribution modes of fractured tight sandstone gas reservoirs are classified into three categories. The influence of random generation of fracture networks on typical well test type curves is discussed. The results of discrete fracture well test model are compared with those of the traditional continuous medium well test model, and the applicable conditions of the traditional continuous medium well test model is determined. Second, there are great differences between the results of discrete fracture model and those of dual porosity medium model. 1 The dual porosity medium model is a special case of the discrete fracture model, in which the fractures are evenly distributed within infinitely small spacing. Third, the characteristics of well test type curves under three fracture network distribution modes are discussed. The well test type curves that cannot be interpreted by the conventional dual/triple porosity continuous medium model are successfully interpreted by using the established well test interpretation model of random discrete fracture. The curve matching effect is ideal and the interpreted parameters are reasonable. In conclusion, the new model and the new method reveal the development mechanism of step-by-step production and coordinated gas supply between media of different scales, explain the development characteristics of large inter-well productivity difference and abnormal rapid inter-well pressure response, and provide a reference for the development of similar gas reservoirs.

The acoustic wave propagation characteristics of carbonate rocks have important application value. The systematic analysis of the effects of fluid type, fluid pressure, temperature and confining pressure on acoustic wave velocity and spectrum characteristics of carbonate rocks still needs to be strengthened. Carbonate rocks with pores and fractures mined from the Dengying Formation in the Hechuan and Tongnan areas, Sichuan Basin, were selected to carry out acoustic transmission experiments under different conditions. The effects of confining pressure, pore pressure, pressure difference, temperature and fluid category on the acoustic velocity of carbonate rocks and the dominant frequency characteristics of transmitted acoustic waves were analyzed. The results show that the sensitivity of acoustic velocity to pressure change in saturated formation water is lower than that in saturated nitrogen. In the process of pressure change, the variation amplitude of acoustic velocity is positively correlated with the porosity of rock samples. Within the experimental temperature range, with increasing temperature, the P-wave velocity and S-wave velocity of the saturated formation water and nitrogen samples decreases lightly. When the differential stress is low, the acoustic velocity corresponding to the way of changing the differential stress by changing the pore pressure is greater than that by changing the confining pressure, and the conclusion is opposite when the differential stress is high. Under the same differential stress condition, the acoustic velocity is more sensitive to changes in the confining pressure than the changes of pore pressure. The included angle and slope difference of the two acoustic velocity-differential stress curves corresponding to constant confining pressure and constant pore pressure can qualitatively reflect the relative size of the dynamic Biot effective stress coefficient of carbonate rock samples. With increasing differential stress, the contribution of pore pressure to effective stress decreases gradually. With increasing pore pressure, the dominant frequency amplitudes of the P-wave and S-wave gradually decrease. With increasing confining pressure, the dominant frequency amplitudes of the P-wave and S-wave gradually increase. With increasing temperature, the dominant frequency amplitudes of the P-wave and S-wave gradually increase. The research results are helpful to the theoretical research and engineering application of pore pressure predictionin carbonate formation based on logging acoustic information.

Abstract In practical road traffic scene, targets usually face high ground clutter, high and variable motion, high nonlinearity, which lead to targets tracking or identification challenging. What’s more, tracking and identification are usually interdependent in reality, and thus it is promising to solve them jointly. In this paper, we propose a novel joint tracking and identification (JTI) scheme to handle such problems involving coupled tracking and identification, i.e., JTI problems. Specifically, we formulate the JTI problem in complex traffic scene using a hybrid system. Then, by exploiting the generalized Bayes risk for JTI, we derive analytical estimator and decider for the coupling of tracking and identification in complex road targets motion. Furthermore, an unscented Kalman filter-expected mode augmentation-based estimation strategy is creatively developed to improve both estimation and decision performance. In additions, a joint performance evaluation metric is presented to assess the performance the joint of the proposed JTI scheme. Finally, two simulation examples under different traffic scenarios demonstrate that the proposed JTI approach outperforms the traditional tracking-then-identification and identification-then-tracking methods in joint performance.

Highlights Progesterone has sex-dependent effects on smoking measures in individuals with Tobacco Use Disorder. Higher conversion of progesterone to allopregnanolone (as indicated by the allopregnanolone:progesterone ratio) was associated with lower nicotine withdrawal in female but not male smokers during a brief abstinence. Higher conversion of progesterone to allopregnanolone was associated with lower ratings of confusion and marginally lower ratings of fatigue in female but not male smokers. Irrespective of sex, higher conversion of progesterone to allopregnanolone was associated with stronger “good effects” and weaker “bad effects” of nicotine during active smoking.

Amyotrophic lateral sclerosis (ALS) is a chronic, progressive neurodegenerative disease characterized by the loss of motor neurons. Dysregulated peripheral immunity has been identified as a hallmark of ALS. Neutrophils, as the front-line responders of innate immunity, contribute to host defense through pathogen clearance. However, they can concurrently play a detrimental role in chronic inflammation. With the unveiling of novel functions of neutrophils in neurodegenerative diseases, it becomes essential to review our current understanding of neutrophils and to recognize the gap in our knowledge about their role in ALS. Thus, a detailed comprehension of the biological processes underlying neutrophil-induced pathogenesis in ALS may assist in identifying potential cell-based therapeutic strategies to delay disease progression.

Abstract Background Polygonatum cyrtonema, one of origins of Polygonata Rhizoma (HuangJing in Chinese), is traditionally steamed repeatedly before being used as herbal medicine in China. However, there has no standard for steaming of HuangJing. Therefore, a comprehensive study for effects of steam on polysaccharides from Polygonatum cyrtonema based on saccharide mapping, a powerful method developed for polysaccharides analysis, and pharmacological activity are still necessary, which is helpful to explore the effect of steam on the physiochemical and biological activities of its polysaccharides and develop steaming standard of Polygonatum cyrtonema. Methods To explore the effect of steam on physiochemical and biological activities of P. cyrtonema polysaccharides (PCP), six polysaccharides named PCP0, PCP1, PCP2, PCP3, PCP4 and PCP5 were extracted from the herb consecutively steamed for 0–5 times, respectively. Their molecular weight distribution, monosaccharide composition and PACE fingerprints were investigated through HPSEC-MALLS-RID, HPAEC-PAD and saccharide mapping based on polysaccharides analysis by using carbohydrate gel electrophoresis (PACE) and HPTLC, respectively. In addition, their antioxidant ability and immunostimulatory activities on RAW 264.7 cells in terms of NO production and phagocytosis were compared. Results Results suggested that molecular weights could be changed during steam, which increased by first steaming and then decreased with further steaming though all polysaccharides’ molecular weights were 105-107 Da. They all showed irregularly spherical conformation in aqueous solution based on AFM imaging. Their monosaccharide composition and PACE fingerprints were significantly different after steaming, i.e., galactose increased while glucose and mannose decreased, and β-1,4-Galp appeared while β-1,4-Manp increased, after steaming. Steamed PCP significantly increased scavenging activity against ABTS radicals, while PCP0 had the best immunostimulatory effect on RAW 264.7 in terms of NO production and phagocytosis. Conclusions In summary, steam significantly affected the chemical composition and bioactivities of polysaccharides from P. cyrtonema. Considering the balance beneficial effects of steaming on antioxidant and immunopotentiation activities of PCP, 2 times of continuous steam is the optimal choice under the given conditions.

Abstract Background With the spread of COVID-19, the time-series prediction of COVID-19 has become a research hotspot. Unlike previous epidemics, COVID-19 has a new pattern of long-time series, large fluctuations, and multiple peaks. Traditional dynamical models are limited to curves with short-time series, single peak, smoothness, and symmetry. Secondly, most of these models have unknown parameters, which bring greater ambiguity and uncertainty. There are still major shortcomings in the integration of multiple factors, such as human interventions, environmental factors, and transmission mechanisms. Methods A dynamical model with only infected humans and removed humans was established. Then the process of COVID-19 spread was segmented using a local smoother. The change of infection rate at different stages was quantified using the continuous and periodic Logistic growth function to quantitatively describe the comprehensive effects of natural and human factors. Then, a non-linear variable and NO2 concentrations were introduced to qualify the number of people who have been prevented from infection through human interventions. Results The experiments and analysis showed the R 2 of fitting for the US, UK, India, Brazil, Russia, and Germany was 0.841, 0.977, 0.974, 0.659, 0.992, and 0.753, respectively. The prediction accuracy of the US, UK, India, Brazil, Russia, and Germany in October was 0.331, 0.127, 0.112, 0.376, 0.043, and 0.445, respectively. Conclusion The model can not only better describe the effects of human interventions but also better simulate the temporal evolution of COVID-19 with local fluctuations and multiple peaks, which can provide valuable assistant decision-making information.

Abstract Multiple myeloma (MM) remains an incurable plasma cell cancer characterized by abnormal secretion of monoclonal immunoglobulins. The molecular mechanism that regulates the drug sensitivity of MM cells is being intensively studied. Here, we report an unexpected finding that the protein encoded by neural precursor cell-expressed developmentally downregulated gene 4L (NEDD4L), which is a HECT E3 ligase, binds the 19S proteasome, limiting its proteolytic function and enhancing autophagy. Suppression of NEDD4L expression reduced bortezomib (Bor) sensitivity in vitro and in vivo, mainly through autophagy inhibition mediated by low NEDD4L expression, which was rescued by an autophagy activator. Clinically, elevated expression of NEDD4L is associated with a considerably increased probability of responding to Bor, a prolonged response duration, and improved overall prognosis, supporting both the use of NEDD4L as a biomarker to identify patients most likely to benefit from Bor and the regulation of NEDD4L as a new approach in myeloma therapy.

Summary: Background: Intratumor heterogeneity (ITH) has been associated with poor prognosis in advanced non-small cell cancer (NSCLC) patients receiving immune checkpoint blockade (ICB) therapies. However, there is currently no evidence supporting an ITH metric as a predictor of clinical benefit from ICB. The unique advantages of blood make it a promising material for ITH estimation and relevant applications. This study aims to develop and validate a blood-based ITH index for predicting ICB response. Methods: NSCLC patients from the OAK and POPLAR clinical trials were used as the training cohorts for algorithm development. Survival analyses with overall survival (OS) and progression-free survival (PFS) as endpoints were performed to assess clinical response. The predictive value of bITH was subsequently validated with an independent cohort of 42 NSCLC patients treated with PD-1 blockade. Findings: bITH was significantly associated with the differential OS and PFS elicited by atezolizumab vs. docetaxel in both univariable and multivariable analyses in the OAK patients, suggesting bITH as an independent predictor for response to ICB. Moreover, compared with blood tumor mutation burden (bTMB), bITH enabled greater OS segregation and comparable PFS segregation, and obtained a predictive role regardless of bTMB status. Moreover, the association between bITH and PFS was validated with an independent cohort. Interpretation: Patients with low blood-based ITH metric manifest significant OS and PFS benefit from immunotherapy versus chemotherapy. Future research is awaited to corroborate our findings and to enrich the clinical utility of ITH. Funding: This study was supported by the National Natural Science Foundation of China (Nos. 81972718 and 81572321), the Natural Scientific Foundation of Zhejiang Province, China (No. LY19H160007), the Science and Technology Program for Health and Medicine in Zhejiang Province, China (No. 2021KY541), the Scientific Research Project, Science and Technology Department of Sichuan Province (No. 21YYJC1616), the Scientific Research Project, Sichuan Medical Association (No. S20002), Wu Jieping Medical Foundation (No. 320.6750), and 2018 Entrepreneurial Leading Talent of Guangzhou Huangpu District and Guangzhou Development District (No. 2022-L023).

Bay areas are special ecological transition zones where land and sea meet, and the ecological health of the region is an essential foundation for sustainable development. Therefore, it is crucial to establish an ecological health evaluation index system to assess the ecological health sustainability in bay areas for developing coastal zone management plans. This study proposes a cross-jurisdiction framework for assessing the ecological health in Xiamen Bay at multi-scales and multi-levels. The entropy weight and comprehensive index methods are then used to evaluate the ecological health in Xiamen Bay coupling ecological integrity and biodiversity with ecosystem services. Finally, a system dynamics model was established to analyze the sustainability of ecological health in Xiamen Bay. The results show that the overall ecological health level in Xiamen Bay continuously maintained

Abstract Background Stimulator of IFN genes (STING) is highly expressed in the livers of non-alcoholic fatty liver disease (NAFLD) patients and high fat diet (HFD) induced NAFLD mice model. The STING signaling-mediated inflammation has been shown to play a critical role in metabolic disorders. Lingguizhugan decoction (LGZG), a Traditional Chinese herbal decoction, has been applied to treat metabolic disorders for many years. However, whether LGZG can alleviate the progression of NAFLD through inhibiting inflammation remains unclear. This study was to determine the role of STING-mediated inflammation in the HFD-induced hepatic-lipid deposition treated with LGZG. Methods The anti-inflammatory and anti-steatotic effects of LGZG in vivo were detected by H&E staining, immunofluorescence and immuno-chemistry. Mice bone-marrow-derived macrophages (BMDMs) and primary liver macrophages were treated with STING-specific agonist (DMXAA), LGZG and its critical components respectively. The treated culture supernatant of BMDMs and primary liver macrophages from each group was co-cultured with palmitic acid-treated mouse primary hepatocytes or mouse liver cell line AML-12 respectively to detect whether the activation of STING-mediated pathway is involved in the anti-steatotic effect of LGZG. The hepatocyte lipid deposition in vivo and in vitro were detected by oil red staining. Mitochondrial DNA release of mouse liver extracts were detected by real time PCR. The expression of proteins and inflammatory cytokines related to STING-TBK1-NF-κB pathway was detected by western blotting and ELISA. Results LGZG significantly ameliorated HFD induced hepatic steatosis, oxidative stress, hepatic mitochondrial damage and mitochondrial DNA release, which was correlated with reduction of the expression level of STING as well as the infiltration of STING-positive macrophages in the livers of HFD fed mice. The critical components of LGZG directly inhibited the activation of STING-TBK1-NF-κB pathway in liver macrophages induced by DMXAA, LPS, thereby reducing the release of IFNβ and TNFα. Co-incubating the culture supernatant of LGZG treated liver macrophages and PA-stimulated hepatocytes significantly inhibited the PA-induced lipid deposition. Conclusion This study demonstrates that LGZG can ameliorate HFD-induced hepatic-lipid deposition through inhibiting STING-TBK1-NF-κB pathway in liver macrophages, which provides novel insight for elucidating the molecular mechanism of LGZG alleviating HFD induced hepatic steatosis.

Abstract RNA demethylase ALKBH5 takes part in the modulation of N6-methyladenosine (m6A) modification and controls various cell processes. ALKBH5-mediated m6A demethylation regulates gene expression by affecting multiple events in RNA metabolism, e.g., pre-mRNA processing, mRNA decay and translation. Mounting evidence shows that ALKBH5 plays critical roles in a variety of human malignancies, mostly via post-transcriptional regulation of oncogenes or tumor suppressors in an m6A-dependent manner. Meanwhile, increasing non-coding RNAs are recognized as functional targets of ALKBH5 in cancers. Here we reviewed up-to-date findings about the pathological roles of ALKBH5 in cancer, the molecular mechanisms by which it exerts its functions, as well as the underlying mechanism of its dysregulation. We also discussed the therapeutic implications of targeting ALKBH5 in cancer and potential ALKBH5-targeting strategies.

Tetrastigma hemsleyanum, a traditional Chinese medicinal plant, possesses various biological activities, including anti-inflammatory and immunomodulatory functions. The purpose of this study was to determine the alleviating effect of the water extract of Tetrastigma hemsleyanum leaves (THLW) on ulcerative colitis (UC) and its relationship with gut microbiota. The administration of THLW significantly decreased the severity of dextran sulfate sodium (DSS)-induced intestinal damage, as demonstrated by the stabilization of body weight and colon length, and decreased disease activity index (DAI) and histological scores. THLW also decreased NF-κB protein expression in colon tissues and reduced the serum levels of IL-6, IL-1β, and TNF-α. Further co-housing experiment confirmed that the anti-UC effect of THLW was possibly by regulating the structure and composition of gut microbiota, including increasing the abundance of Oscillospiraceae, Prevotellaceae and Corynebacterium. Additionally, the expression of genes related to inflammation and immunity was also regulated by THLW treatment as evidenced by transcriptome analysis. These results suggested that the protective effect of THLW on DSS-induced colitis was mediated by alleviating inflammation and modulating the microbiota composition. This work proved the potent protective effects of THLW treatment on colitis and may have potential for UC relief.

Multiple myeloma (MM) is characterized by an accumulation of monoclonal plasma cells within the bone marrow (BM). Macrophages are an abundant component of myeloma BM microenvironment and support survival of the malignant cells and foster myeloma development and progression by suppression of the immune response. In our previous study, we found that MM patients overexpress pro-inflammatory cytokine interleukin-32 (IL-32). The present study aimed to investigate the role of IL-32 in myeloma progression and mechanisms of IL-32 on macrophages functions. We discovered that the expression of IL-32 was associated with the disease stage in myeloma patients. MM-derived exosomes containing IL-32γ promoted the expression of programmed death-ligand 1(PD-L1) by macrophages, thus promoting immune evasion. Mechanistically, myeloma-secreted IL-32γ acted via proteinase 3 (PR3) to enhance 6-phosphofructo-2-kinase/fructose-2,6-biphosphatase 3 (PFKFB3) dependent glycolysis and subsequent PD-L1 expression. Moreover, the PFKFB3-Janus kinase 1 (JAK1) axis might contribute to the expression of PD-L1 by macrophages. To sum up, we concluded that IL-32 was a critical mediator in myeloma progression, and targeting IL-32 signaling might be used as a potential strategy for treating myeloma.

IntroductionFrequent exacerbation phenotype of chronic obstructive pulmonary disease (COPD) represents a more concerning disease subgroup requiring better prevention and intervention, of which airway microbiome provides new perspective for further exploration.MethodsTo investigate whether frequent exacerbators of COPD have distinguishable sputum microbiome during clinical stability, COPD patients at high disease grades with or without frequent exacerbation were recruited for sputum microbiome analysis. Sputum samples were collected during clinical stability and underwent 16S rRNA sequencing, which was then subjected for amplicon sequence variants (ASVs)-based microbiome analysis.ResultsOur results revealed that compared with healthy controls and infrequent exacerbators, frequent COPD exacerbators have distinguishably dysbiotic sputum microbiome, as featured by fewer ASVs features, lower alpha diversity, distinct beta diversity patterns. Further taxonomic compositional analysis illustrated the structural distinctions between frequent COPD exacerbators and infrequent exacerbators at differential taxa levels and highlighted Stenotrephomonas due to its prominent elevation in frequent COPD exacerbators, providing a promising candidate for further exploration of microbiome biomarker. Moreover, we also demonstrated that frequent exacerbation phenotype is distinguishable from infrequent exacerbation phenotype with respect of functional implications.ConclusionOur study demonstrated the first positive correlation between the frequent exacerbation phenotype of COPD and the sputum microbiome during clinical stability in a single-center Chinese COPD cohort and provide potential diagnostic and therapeutic targets for further investigation.

ObjectiveThe aim of this study was to examine the effects of psychological distance on spontaneous justice inferences.MethodsTwo experiments were conducted using the probe recognition paradigm to directly examine whether psychological distance affects spontaneous justice inferences. In Experiment 1, the spatial distance of justice actions from the perceivers was manipulated. In Experiment 2, temporal distance was manipulated.ResultsConsistent with our expectations, the results of Experiments 1 and 2 (for spatial distance and temporal distance, respectively) consistently demonstrated the effect of psychological distance on spontaneous justice inferences. In concrete terms, participants made stronger spontaneous justice inferences when confronted with situation descriptions of justice-implying events occurring in a spatially distant location than in a proximal location (Experiment 1) and in the distant-future condition than in the near-future condition (Experiment 2).ConclusionThese findings indicate that psychological distance can influence influence simplicity, unintentional processing of justice inferences.

The artificial bee colony algorithm (ABC) is a promising metaheuristic algorithm for continuous optimization problems, but it performs poorly in solving discrete problems. To address this issue, this paper proposes a hybrid discrete artificial bee colony (HDABC) algorithm based on label similarity for the point-feature label placement (PFLP) problem. Firstly, to better adapt to PFLP, we have modified the update mechanism for employed bees and onlooker bees. Employed bees learn the label position of the better individuals, while onlooker bees perform dynamic probability searches using two neighborhood operators. Additionally, the onlooker bees’ selection method selects the most promising solutions based on label similarity, which improves the algorithm’s search capabilities. Finally, the Metropolis acceptance strategy is replaced by the original greedy acceptance strategy to avoid the premature convergence problem. Systematic experiments are conducted to verify the effectiveness of the neighborhood solution generation method, the selection operation based on label similarity, and the Metropolis acceptance strategy in this paper. In addition, experimental comparisons were made at different instances and label densities. The experimental results show that the algorithm proposed in this paper is better or more competitive with the compared algorithm.

To address the challenges of efficient state monitoring of lithium-ion batteries in electric vehicles, a co-estimation algorithm of state-of-charge (SOC) and state-of-health (SOH) is developed. The algorithm integrates techniques of adaptive recursive least squares and dual adaptive extended Kalman filtering to enhance robustness, mitigate data saturation, and reduce the impact of colored noise. At 25 °C, the algorithm is tested and verified under dynamic stress test (DST) and Beijing bus DST conditions. Under the Beijing bus DST condition, the algorithm achieves a mean absolute error (MAE) of 0.17% and a root mean square error (RMSE) of 0.19% for SOC estimation, with a convergence time of 4 s. Under the DST condition, the corresponding values are 0.05% for MAE, 0.07% for RMSE, and 5 s for convergence time. Moreover, in this research, the SOH is described as having internal resistance. Under the Beijing bus DST condition, the MAE and the RMSE of the estimated internal resistance of the proposed approach are 0.018% and 0.075%, with the corresponding values of 0.014% and 0.043% under the DST condition. The results of the experiments provide empirical evidence for the challenges associated with the efficacious estimation of SOC and SOH.

Abstract It is usually seen that DC flashover voltage of the water droplet on the surface of silicone rubber (SIR) composite insulator is lower than AC flashover voltage. It is necessary to study the mechanisms and influencing factors of the surface properties. In this article, experiments are performed to study the moving processes of the water droplet and the influences of its dynamic behaviours on flashover voltage under DC/AC electric field. Besides, an electrohydrodynamic coupling method is employed to establish the simulating model. Moreover, the theoretical physical model is established to reveal the mechanisms of dynamic behaviours of a droplet. It is indicated that the simulation results are in good consistency with the experimental data. The elongation behaviours of a droplet on the surface of a composite insulator can influence the homogeneity of the electric field distribution along the sample's surface. It is shown that the different dynamic behaviours and flashover performances for a single water droplet on the SIR surface are both affected by the volume of the droplet and the type of voltage applied.

Abstract In eukaryotes, histones and their variants are essential for chromatin structure and function; both play important roles in the regulation of gene transcription, as well as the development of tumors. We aimed to explore the genomics data of hepatocellular carcinoma (HCC), combined with literature analysis, in terms of the histone variant H2A.Z. Cell phenotype assay confirmed the effect of H2A.Z on the proliferation, metastasis, apoptosis, and cell cycle of HCC cells. H2A.Z was shown to function via the tumor dysregulation signaling pathway, with BCL6 as its interacting protein. In addition, the acetylation level of H2A.Z was higher in HCC and was related to tumor formation. We found the acetylation of H2A.Z to be related to and regulated by lincZNF337-AS1. LincZNF337-AS1 was found to bind to H2A.Z and KAT5 at different sites, promoting the acetylation of H2A.Z through KAT5. We concluded that, in HCC, H2A.Z is an oncogene, whose acetylation promotes the transcription of downstream genes, and is regulated by lincZNF331-AS1.

Background: Systematically assessing the causal associations between medications and neurodegenerative diseases is significant in identifying disease etiology and novel therapies. Here, we investigated the putative causal associations between 23 existing medication categories and major neurodegenerative diseases (NDs), including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). Methods: A two-sample mendelian randomization (MR) approach was conducted. Estimates were calculated using the inverse-variance weighted (IVW) method as the main model. A sensitivity analysis and a pleiotropy analysis were performed to identify potential violations. Results: Genetically predisposition to antihypertensives (OR = 0.809, 95% CI = 0.668–0.981, p = 0.031), thyroid preparations (OR = 0.948, 95% CI = 0.909–0.988, p = 0.011), and immunosuppressants (OR = 0.879, 95% CI = 0.789–0.979, p = 0.018) was associated with a decreased risk of AD. Genetic proxies for thyroid preparations (OR = 0.934, 95% CI = 0.884–0.988, p = 0.017), immunosuppressants (OR = 0.825, 95% CI = 0.699–0.973, p = 0.022), and glucocorticoids (OR = 0.862, 95% CI = 0.756–0.983, p = 0.027) were causally associated with a decreased risk of PD. Genetically determined antithrombotic agents (OR = 1.234, 95% CI = 1.042–1.461, p = 0.015), HMG CoA reductase inhibitors (OR = 1.085, 95% CI = 1.025–1.148, p = 0.005), and salicylic acid and derivatives (OR = 1.294, 95% CI = 1.078–1.553, p = 0.006) were associated with an increased risk of ALS. Conclusions: We presented a systematic view concerning the causal associations between medications and NDs, which will promote the etiology discovery, drug repositioning and patient management for NDs.

In the era of big data, a significant volume of spatiotemporal data exists in a multiscale format, describing diverse phenomena in the objective world across different spatial and temporal scales. While existing methods focus on analyzing the features and connections of spatiotemporal data at various scales, they often overlook the consideration of uncertainty in spatiotemporal information within the context of multiscale meaning. To effectively harness the potential of spatiotemporal data, it becomes crucial to capture the fuzzy spatiotemporal information inherent in multiscale datasets. This paper proposes a novel multiscale spatiotemporal correlation method that accounts for and quantifies the uncertainty of spatiotemporal information. Spatiotemporal information is categorized into two types, explicit information and implicit information, based on respective levels of uncertainty. The method employs spatiotemporal cubes to interpret the spatiotemporal items within the data, followed by the introduction of a benchmark scale to determine the certainty of each spatiotemporal item based on its range and topological relationships. Subsequently, spatiotemporal confidence and correlation index are proposed to gauge the significance of geographical elements and their interrelationships. To validate the proposed method, a multiscale spatiotemporal transaction dataset is generated and utilized in the experiment. The experimental results demonstrate that the proposed method effectively captures spatiotemporal implicit information and enables better utilization of multiscale spatiotemporal data. Notably, the importance of each object of study varies when analyzed using different benchmark scales, providing valuable insights for professionals to identify novel objects and associations worthy of consideration. The obtained results can be used to construct spatiotemporal knowledge graphs.

BackgroundAt present, immunotherapy has become an important treatment for lung cancer. With the widespread use of immune checkpoint inhibitors (ICIs), we must be strict with the emergence of immune related adverse events (irAEs). There are also some patients who do not respond to immunotherapy. However, there was no biomarkers to predict the safety and efficacy of immunotherapy. The selection of immunotherapy beneficiaries contributes to improving the efficacy and safety of lung cancer treatment.MethodThe electronic medical records of 221 lung cancer patients with complete clinical data who received immunotherapy from the First Affiliated Hospital of Xi ‘an Jiaotong University from November 2020 to October 2021 were collected and followed up. IBM SPSS Statistic 26.0 and R 4.1.2 software were used for statistical analysis and mapping.Results1. A total of 221 lung cancer patients receiving immunotherapy were included in the study. Higher baseline levels of IL-1β (7.88 vs 16.16pg/mL, P=0.041) and IL-2 (1.28 vs 2.48pg/mL, P=0.001) were significantly associated with irAEs. Higher levels of IL-5 (2.64 vs 5.68pg/mL, P=0.013), IFN-α (1.70 vs 3.56pg/mL, P=0.004) and IFN-γ (6.14 vs 21.31pg/mL, P=0.022) after the first cycle therapy were associated with irAEs. There was no statistical significance between cytokines and irAEs after the second cycle therapy. Higher IL-5 levels in peripheral blood (9.50 vs 3.57pg/mL, P=0.032) were associated with the occurrence of irAEs after the third cycle therapy. 2.The efficacy of immunotherapy was assessed in 142 lung cancer patients. There was no statistical significance between baseline cytokine levels and clinical benefit. After the first cycle therapy, the level of serum cytokines had no statistical significance with the occurrence of immunotherapy clinical benefit. Lower serum levels of IL-10 (2.66 vs 1.26pg/mL, P=0.016) and IL-17 (8.47 vs 2.81pg/mL, P=0.015) were associated with clinical benefit after the second cycle therapy. Lower serum levels of IL-6 (10.19 vs 41.07pg/mL, P=0.013) and IL-8 (8.01 vs 17.22pg/mL, P=0.039) were associated with clinical benefit of immunotherapy after the third cycle therapy.Conclusion1. Baseline IL-1β and IL-2 levels in peripheral blood were associated with the occurrence of irAEs in lung cancer patients. The levels of IL-5, IFN-α and IFN-γ during treatment were associated with irAEs. 2. Baseline cytokine levels in peripheral blood were not associated with immunotherapy efficacy. The levels of IL-6, IL-8, IL-10, and IL-17 levels during treatment were associated with immunotherapy efficacy.

BackgroundIn this study, we investigated the epidemiological characteristics and predictors of diabetic peripheral neuropathy (DPN) in adult patients with type 2 diabetes mellitus (DM).MethodsThe study was designed as a retrospective cohort trial at the First Affiliated Hospital of Wenzhou Medical University. From January 2017 to December 2020, a total of 1,262 patients with DM were enrolled to assess the risk factors for DPN. The patients were divided into two groups (DPN group and non-DPN group). The Mann–Whitney U test or t-test, receiver operating characteristic (ROC) analyses, univariate chi-square analyses, and multiple logistic regression analyses were used to analyze the adjusted predictors of DPN.ResultsThe overall prevalence of DPN in DM patients was 72.7% (n = 793/1,091). Multivariate analysis revealed that age > 66 years (odds ratio [OR], 2.647; 95% confidence interval [CI] 1.469–4.770; p = 0.002), history of hypertension (OR, 1.829; 95% CI 1.146–2.920; p = 0.011), neutrophil (NE) levels exceeding 4.0 × 109/L (OR 0.256; 95% CI 0.162–0.405; p = 0.001), lymphocyte (LY) levels over 3.0 × 109/L (OR 7.173; 95% CI 4.258–12.086; p = 0.000), HbA1c > 7.7% (OR 3.151; 95% CI 1.959–5.068; p = 0.000), and FT3 > 4.4 pmol/L (OR 0.417; 95% CI 0.263–0.662; p = 0.000) were six significant predictive factors for the prevalence of DPN.ConclusionsHigh levels of LY, HbA1c, history of hypertension, and > 66 years of age increase the risk of DPN in adult patients with DM, while high levels of NE and FT3 were protective factors of DPN. Thus, the prediction of DPN can significantly be improved by identifying older patients over the age of 66 and history of hypertension, as well as establishing the biochemical cutoff values of NE, LY, HbA1c, and FT3.

As the thermal variation may change the total electron emission yield (TEEY) of materials and may ultimately result in unexpected surface charging, it is necessary to study the TEEY at various temperatures. In this research, we first updated the TEEY measurement system with a newly designed sample stage for different temperatures (−50, 25, and 100 °C) and the primary electron from 25 eV to 10 keV. By using the 30 μs/20 nA primary electron beam and sample scanning method to mitigate surface charging, the TEEY could be accurately obtained for dielectrics. Then, we chose a kind of polyimide film (Kapton 100H) used on spacecraft and a gold film sample to compare the TEEY at various temperatures. The results show that high temperature leads to higher TEEY of Kapton films, whereas 25 and −50 °C also leads to the same. On the other hand, the TEEY of gold remains the same at different temperatures. In the view of surface hole density and charge transportation, the TEEY variation of Kapton films was analyzed by bulk conduction, charge mobility, and the electron–hole recombination property. It is considered that the dissipation rate of holes is sensitive to temperature, and furthermore, the TEEY of Kapton films is dependent on temperature.