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Abstract Metabolic enzymes perform moonlighting functions during tumor progression, including the modulation of chemoresistance. However, the underlying mechanisms of these functions remain elusive. Here, utilizing a metabolic clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 knockout library screen, we observe that the loss of glutamate-cysteine ligase modifier subunit (GCLM), a rate-limiting enzyme in glutathione biosynthesis, noticeably increases the sensitivity of colorectal cancer (CRC) cells to platinum-based chemotherapy. Mechanistically, we unveil a noncanonical mechanism through which nuclear GCLM competitively interacts with NF-kappa-B (NF-κB)-repressing factor (NKRF), to promote NF-κB activity and facilitate chemoresistance. In response to platinum drug treatment, GCLM is phosphorylated by P38 MAPK at T17, resulting in its recognition by importin a5 and subsequent nuclear translocation. Furthermore, elevated expression of nuclear GCLM and phospho-GCLM correlate with an unfavorable prognosis and poor benefit from standard chemotherapy. Overall, our work highlights the essential nonmetabolic role and posttranslational regulatory mechanism of GCLM in enhancing NF-κB activity and subsequent chemoresistance.

As an inherent characteristic of synthetic aperture radar (SAR) systems, the presence of speckle noise reduces the signal-to-noise ratio (SNR) of SAR images, leading to blurred image details and limiting the accuracy of change detection in SAR images. For C-band SAR images, different satellite imaging and ground object reflections can produce varying levels of noise, necessitating a network design adaptable to different noise levels. In this study, we introduce a focal loss function to enhance the robustness of the network, allowing for high-precision change detection of SAR images with different noise levels through parameter adjustment. To address the issue of low SNR in SAR images, we construct a deep learning network focused on feature exploration and utilization to effectively distinguish between noise and change information. The model initially employs discrete wavelet decomposition to extract high-frequency bands for noise reduction. Subsequently, conventional convolutions are utilized to extract high-level semantic information from frequency-domain images, with the resulting feature maps serving as patch inputs to the ConvMixer module to acquire blended spatial and positional information. In the decoder phase, valuable encoder features from multiscale attention gates are concatenated with corresponding upsampled features to select encoder features based on different resolutions adaptively. Through comparative experiments on real datasets, the superiority of the model is demonstrated.

Abstract Designing catalysts with well-defined, identical sites that achieve site-specific selectivity, and activity remains a significant challenge. In this work, we introduce a design principle of topological-single-atom catalysts (T-SACs) guided by density functional theory (DFT) and Ab initio molecular dynamics (AIMD) calculations, where metal single atoms are arranged in asymmetric configurations that electronic shield topologically misorients d orbitals, minimizing unwanted interactions between reactants and the support surface. Mn1/CeO2 catalysts, synthesized via a charge-transfer-driven approach, demonstrate superior catalytic activity and selectivity for NO x removal. A life-cycle assessment (LCA) reveals that Mn1/CeO2 significantly reduces environmental impact compared to traditional V-W-Ti catalysts. Through in-situ spectroscopic characterizations combined with DFT calculations, we elucidate detailed reaction mechanisms. This study establishes T-SACs as a promising class of catalysts, offering a systematic framework to address catalytic challenges by defining site characteristics. The concept highlights their potential for advancing selective catalytic processes and promoting sustainable technologies.

Abstract The field of radiology is currently undergoing revolutionary changes owing to the increasing application of artificial intelligence (AI). This scoping review identifies and summarizes the technical methods and clinical applications of AI applied to magnetic resonance imaging of cerebrovascular diseases (CVDs). Preferred Reporting Items for Systematic reviews and Meta‐Analyses extension for Scoping Reviews was adopted and articles listed in PubMed and Cochrane databases from January 1, 2018 to December 31, 2023, were assessed. In total, 67 articles met the eligibility criteria. We obtained a general overview of the field, including lesion types, sample sizes, data sources, and databases and found that nearly half of the studies used multisequence magnetic resonance as the input. Both classical machine learning and deep learning were widely used. The evaluation metrics varied according to the five main algorithm tasks of classification, detection, segmentation, estimation, and generation. Cross‐validation was primarily used with only one third of the included studies using external validation. We also illustrate the key questions of the CVD research studies and grade the clinical utility of their AI solutions. Although most attention is devoted to improving the performance of AI models, this scoping review provides information on the availability of algorithms, reliability of external validations, and consistency of evaluation metrics and may facilitate improved clinical applicability and acceptance.

Objective:. To investigate the perceptions of pancreatic surgeons regarding palliative care for pancreatic cancer and the current status of palliative care for pancreatic cancer patients in China. Methods:. An online questionnaire consisting of 35 questions in 5 domains, including basic information of the respondents, personal interest, training and experiences of palliative care, recognition of the importance of palliative care, palliative care in the hospital of the respondents, and advice to improve the service of palliative care for pancreatic cancer, was distributed to pancreatic surgeons by the WeChat APP. All the data were automatically recorded and can be downloaded. The respondents’ perceptions of palliative care and the current status of palliative care were depicted, and the factors influencing the perceptions of the respondents and palliative care in hospitals were further analyzed. Results:. Responses from 429 pancreatic surgeons were validated. 81.4% were from tertiary hospitals, and 18.6% were from secondary hospitals. 94.2% were from general hospitals, and 5.8% were from cancer hospitals. Most surgeons have worked for over 5 years (93%), 72% had senior titles, and 54.5% held administrative positions. 49% have not read papers on palliative care before. 73.4% of the hospitals did not have a palliative care team, 77.9% did not have specific ward or bed for palliative care, 76.2% of the surgeons thought palliative care needed more attention in their hospitals. 97.4% of the surgeons thought palliative care was important for pancreatic cancer patients, and 94.9% were willing to join the palliative team. 46.6% of the surgeons thought palliative care should be conducted once pancreatic cancer was diagnosed. Most surgeons thought palliative care was helpful and should be involved in the multidisciplinary team. Regarding the geographical differences, surgeons and hospitals in North China performed better than in other regions. Surgeons with experience in clinical trials of pancreatic cancer performed better. The top 3 advice from the surgeons to promote palliative care were more education and training, seminars, and public broadcasting. 69.9% of the surgeons have concerns about the legal issue of implementation of palliative care. Conclusion:. In general, the majority of pancreatic surgeons in China lack training and experience in palliative care for pancreatic cancer, and the current status of palliative care in most hospitals needs to be further improved. Prevalence of the participants think that palliative care is very important for pancreatic cancer patients. Palliative care should be provided once pancreatic cancer is diagnosed, and palliative care should be involved in the multidisciplinary team. More seminars, education and training, and public broadcasting are practical ways to improve palliative care for pancreatic cancer patients.

Abstract In Song dynasty, Dou-Gong construction techniques, Tou-Xin-Zao and Ji-Xin-Zao, varied by the number of Fang connecting to the exterior. This study examines the impact of Fang connections on the mechanical characteristics of Dou-Gong. Six full-scale models were constructed and subjected to quasi-static loading tests in the horizontal Beam and Fang directions under vertical load. The hysteresis behavior, deformation, and stiffness variations were obtained and analyzed. The test results revealed the hysteresis curve of Dou-Gong developed into a flat shape, with good deformation recovery ability and seismic performance. Beam-direction loading led to brittle failure, with Dou-Gong having fewer Fang experiencing bearing capacity loss and those with more Fang succumbing to overturning. Beam-direction stiffness rose by approximately 29% as the number of connecting Fang increased. Fang-direction loading induced ductile failure, predominantly characterized by overturning. Notably, Fang-direction stiffness remained largely unchanged by the varying number of connecting Fang. Dou-Gong slip deformation ratio decreased by 5 -10% as the number of Fang increased. Furthermore, Fang-direction exhibited about 10% greater slip deformation capacity than the Beam-direction. Based on the force transfer mechanism of Dou-Gong components, a stiffness formula for the elastic stage of Dou-Gong in the Beam-direction and Fang-direction was established and validated against experimental data.

The diagnosis of cancer is typically based on histopathological sections or biopsies on glass slides. Artificial intelligence (AI) approaches have greatly enhanced our ability to extract quantitative information from digital histopathology images as a rapid growth in oncology data. Gynecological cancers are major diseases affecting women's health worldwide. They are characterized by high mortality and poor prognosis, underscoring the critical importance of early detection, treatment, and identification of prognostic factors. This review highlights the various clinical applications of AI in gynecological cancers using digitized histopathology slides. Particularly, deep learning models have shown promise in accurately diagnosing, classifying histopathological subtypes, and predicting treatment response and prognosis. Furthermore, the integration with transcriptomics, proteomics, and other multi-omics techniques can provide valuable insights into the molecular features of diseases. Despite the considerable potential of AI, substantial challenges remain. Further improvements in data acquisition and model optimization are required, and the exploration of broader clinical applications, such as the biomarker discovery, need to be explored.

The purpose of this paper is to examine whether green finance and innovation are the drivers of carbon neutrality in China. In this study, a time-varying parametric vector autoregressive model with a stochastic fluctuation term is used to fully examine the evolving relationships among green finance, inputs for innovation, and the process of achieving carbon neutrality. The findings from the empirical research indicate that the advancement of green finance provides a consistent and enduring benefit to the ongoing process of carbon neutralization, while increasing innovation input can also achieve this positive contribution, but the impact is not as strong and sustainable as that of green finance. Moreover, in addition to the direct effects mentioned above, the results of this paper also demonstrate the positive contribution of increased innovative inputs to the development of green finance, and the tendency of this effect to expand in the future as time progresses. Against the backdrop of climate change, which poses a serious challenge to global development, the findings of this paper provide some practical insights into how China can achieve its carbon neutrality goal through the development of green finance and increased investment in innovation.

The diterpene ent-copalol is an important precursor to the synthesis of andrographolide and is found only in green chiretta (Andrographis paniculata). De novo biosynthesis of ent-copalol has not been reported, because the catalytic activity of ent-copalyl diphosphate synthase (CPS) is very low in microorganisms. In order to achieve the biosynthesis of ent-copalol, Saccharomyces cerevisiae was selected as the chassis strain, because its endogenous mevalonate pathway and dephosphorylases could provide natural promotion for the synthesis of ent-copalol. The strain capable of synthesizing diterpene geranylgeranyl pyrophosphate was constructed by strengthening the mevalonate pathway genes and weakening the competing pathway. Five full-length ApCPSs were screened by transcriptome sequencing of A. paniculata and ApCPS2 had the best activity and produced ent-CPP exclusively. The peak area of ent-copalol was increased after the ApCPS2 saturation mutation and its configuration was determined by NMR and ESI-MS detection. By appropriately optimizing acetyl-CoA supply and fusion-expressing key enzymes, 35.6 mg/L ent-copalol was generated. In this study, de novo biosynthesis and identification of ent-copalol were achieved and the highest titer ever reported. It provides a platform strain for the further pathway analysis of andrographolide and derivatives and provides a reference for the synthesis of other pharmaceutical intermediates.

Next-generation sequencing has revolutionized cancer genomics by enabling high-throughput mutation screening yet detecting fusion genes reliably remains challenging. Long-read sequencing offers potential for accurate fusion transcript identification, though challenges persist. In this study, we present an optimized workflow using nanopore sequencing technology to precisely identify fusion transcripts. Our approach encompasses a tailored library preparation protocol, data processing, and fusion gene analysis pipeline. We evaluated the performance using Universal Human Reference RNA and human adenocarcinoma cell lines. Our optimized nanopore sequencing workflow generated high-quality full-length transcriptome data characterized by an extended length distribution and comprehensive transcript coverage. Validation experiments confirmed novel fusion events with potential clinical relevance. Our protocol aims to mitigate biases and enhance accuracy, facilitating increased adoption in clinical diagnostics. Continued advancements in long-read sequencing promise deeper insights into fusion gene biology and improved cancer diagnostics.

The cladding layer of high entropy alloy (HEA), specifically AlCoCrFeNiMo, was fabricated using both continuous wave (CW) and pulse wave (PW) laser techniques, with pulse frequencies set at 0.5 Hz, 5 Hz, 50 Hz, 500 Hz, and 5000 Hz. The microstructure of the cladding layer was analyzed using X-ray diffraction, ultra-depth-of-field metallographic microscopy, and scanning electron microscopy. The wear resistance, corrosion resistance, and combined corrosion-wear resistance of the cladding layer were assessed using friction and wear tests, electrochemical corrosion tests, and corrosion-wear experiments. Additionally, the impact of pulse frequency on the microstructure and properties of HEA cladding layers was examined and compared with CW cladding layers. The research results indicate the presence of body-centered cubic (BCC), σ, and B2 phases in all cladding layers. Compared to the CW cladding layer, the PW cladding layer exhibits smaller grain sizes and a reduced proportion of the σ phase. With an increase in pulse frequency, there is a gradual increase in the proportion of the σ phase and a corresponding evolution in the grain sizes within the HEA cladding structure. Notably, at a specific pulse frequency of 50 Hz, the grain size reaches its minimum. PW cladding exhibited superior wear resistance, corrosion resistance, and corrosion-wear resistance compared to CW cladding, primarily due to the finer grain size observed in the former. The optimal performance of the cladding layer can be achieved when the pulse frequency was set at 50 Hz. The refinement of grain size, combined with an appropriate presence of the σ phase, synergistically contributes to enhancing cutting resistance during friction processes. This collaborative effect further hinders plastic deformation, consequently improving the wear resistance of HEA cladding. Furthermore, the grain refinement in PW cladding promotes the development of surface oxide films, which play a crucial role in reducing galvanic corrosion of alloying elements and minimizing oxygen atom diffusion rates during corrosion processes. Consequently, both corrosion resistance and corrosion wear resistance of PW cladding are significantly enhanced.

Abstract Background Adverse pregnancy outcomes have reached epidemic proportions in recent years with serious health ramifications, especially for diverse cancers risk. Therefore, we carried out an umbrella review to systematically evaluate the validity and strength of the data and the extent of potential biases of the established association between adverse pregnancy outcomes and cancers risk in both mother and offspring. Methods PubMed, Embase, and Web of Science databases were searched from inception until 18 January 2024. Meta-analyses of observational studies investigating the relationship between adverse pregnancy outcomes and multiple cancers risk in both mother and offspring were included. Evidence certainty was assessed using Grading of Recommendations, Assessment, Development, and Evaluation. The protocol for this umbrella review was prospectively registered in PROSPERO (CRD42023470544). Results The search identified 129 meta-analyses of observational studies and 42 types of cancer. Moderate certainty of evidence, exhibiting statistical significance, has been observed linking per kilogram increase in birth weight to a heightened risk of breast cancer (OR = 1.07, 95% CI = 1.02–1.12), prostate cancer (OR = 1.02, 95% CI = 1.00–1.05), leukemia (OR = 1.18, 95% CI = 1.13–1.23), and acute lymphoblastic leukemia in offspring (OR = 1.18, 95% CI = 1.12–1.23); rubella infection during pregnancy to an increased risk of leukemia in offspring (OR = 2.79, 95% CI = 1.16–6.71); and a linear dose–response association between an increase in the proportion of optimal birth weight and an elevated risk of acute lymphoblastic leukemia in offspring (OR = 1.16, 95% CI = 1.09–1.24), respectively. Conclusions Although some adverse pregnancy outcomes have clinically promising associations with risk of several cancers in both mother and offspring, it is essential to conduct additional research to solidify the evidence, evaluate causality, and ascertain clinical utility.

Abstract In the U(1) X SSM, we delve into the quark flavor violation of h → bs, where h is identified as the SM-like Higgs boson discovered at the LHC. As the U(1) extension of the minimal supersymmetric standard model (MSSM), the U(1) X SSM has new super fields such as right-handed neutrinos and three Higgs singlets. We conduct a thorough analysis of the underlying mechanisms and parameter dependencies of h → bs in the U(1) X SSM. In the U(1) X SSM, we discover that the Br(h → bs) for the Higgs decay to bs could significantly differ from the expectation in the standard model (SM), depending on the values of the new parameters introduced in the model. Our research not only contributes to a deeper understanding of Higgs physics within the U(1) X SSM, but also provides valuable guidance for new physics (NP).

Abstract Tungsten oxide (WO3)-based memristors show promising applications in neuromorphic computing. However, single-layer WO3 memristors suffer from issues such as weak memory performance and nonlinear conductance variations. In this work, a functional layer based on the hybrids of WO3−x and TiO2 is proposed for constructing flexible memristors featuring outstanding synaptic characteristics. Applying diverse electrical stimulations to the memristor enables a range of synaptic functions, elucidating its conduction mechanism through the conductive filament model. The incorporation of TiO2 not only enhances the memristor’s memory characteristics but makes its conductance more linear, symmetrical and uniform during the long-term changes. Furthermore, in view of the enhanced device performance by TiO2 doping, the potential of this device for simple behavioral simulation and processing of complex computing problems is explored. The “learning-forgetting-relearning” characteristics and device integrability are visually demonstrated. Applying the device to a convolutional neural network, the recognition accuracy of MNIST handwritten digits reaches 98.7%.

Abstract Background This study aims to elucidate the significance of the preoperative fibrinogen to pre-albumin ratio (FPR) in predicting the prognosis of pancreatic ductal adenocarcinoma (PDAC), a correlation not extensively explored previously. Methods A cohort of 563 patients diagnosed with PDAC and subjected to radical surgical resection was examined. We meticulously documented a range of inflammatory markers, clinical-pathological features, and oncological outcomes. The prognostic value of preoperative FPR was assessed using Kaplan–Meier survival analysis and Cox proportional hazards regression modeling. Furthermore, the predictive accuracy of FPR was evaluated through time-dependent receiver operating characteristic (ROC) curves and decision curve analyses (DCA). Results The determined optimal threshold for FPR was 14.77, which facilitated the stratification of patients into groups with low and high FPR levels. Notably, patients in the high FPR cohort exhibited significantly reduced recurrence-free survival (RFS) and overall survival (OS) rates compared to their low FPR counterparts. Multivariate Cox regression analysis underscored FPR as an independent prognostic indicator for both RFS and OS. In comparison to the neutrophil-to-lymphocyte ratio (NLR), FPR demonstrated superior prognostic accuracy and clinical utility. Conclusion The preoperative fibrinogen to pre-albumin ratio serves as an independent prognostic marker for RFS and OS among PDAC patients undergoing radical resection. Our findings suggest that FPR could be a valuable addition to the current prognostic models, potentially guiding therapeutic decision-making and patient management strategies in PDAC.

Objective: Little progress has been made in recent years using first-line chemotherapy, including gemcitabine combined with nab-paclitaxel, FOLFIRINOX, and NALIRIFOX, for advanced pancreatic adenocarcinoma (APC). In addition, the optimal second-line chemotherapy regimen has not been determined. This study aimed to compare the effectiveness of different types of second-line chemotherapy for APC. Methods: Patients with APC who received first-line treatment from January 2008 to January 2021 were considered eligible for this retrospective analysis. The primary and secondary endpoints were overall survival (OS) and progression-free survival (PFS), respectively. Results: Four hundred and thirty-seven and 617 patients were treated with 5-fluorouracil- and gemcitabine-based chemotherapy as first-line treatment, respectively. Demographic and clinical features, except age and liver metastasis, were comparable between the two groups (P < 0.05). The median OS was 8.8 and 7.8 months in patients who received a 5-fluorouracil- and gemcitabine-based combined regimen for first-line therapy, respectively (HR = 1.244, 95% CI = 1.090–1.419; P < 0.001). The median OS was 5.6 and 1.9 months in patients who received second-line chemotherapy and supportive care, respectively (HR = 0.766, 95% CI = 0.677–0.867; P < 0.001). The median PFS was not significantly differently between gemcitabine or 5-fluorouracil monotherapy and combination therapy. Conclusions: A 5-fluorouracil- or gemcitabine-based combined regimen was shown to be as effective as a single 5-fluorouracil or gemcitabine regimen as second-line therapy for patients with APC.

Abstract The existing deep estimation networks often overlook the issue of computational efficiency while pursuing high accuracy. This paper proposes a lightweight self-supervised network that combines convolutional neural networks (CNN) and Transformers as the feature extraction and encoding layers for images, enabling the network to capture both local geometric and global semantic features for depth estimation. First, depth-separable convolution is used to construct a dilated convolution residual module based on a shallow network to improve the shallow CNN feature extraction receptive field. In the transformer, a multidepth separable convolution head transposed attention module is proposed to reduce the computational burden of spatial self-attention. In the feedforward network, a two-step gating mechanism is proposed to improve the nonlinear representation ability of the feedforward network. Finally, the CNN and transformer are integrated to implement a depth estimation network with a local-global context interaction function. Compared with other lightweight models, this model has fewer model parameters and higher estimation accuracy. It also has better generalizability for different outdoor datasets. Additionally, the inference speed can reach 87 FPS, achieving better real-time performance and accounting for both inference speed and estimation accuracy.

Gestational diabetes mellitus (GDM), which refers to diabetes mellitus or abnormal glucose tolerance of any degree occurring during pregnancy, is a distinct type within the diabetes classification. 25-hydroxyvitamin D deficiency has been associated with an increased risk of maternal glycaemia, insulin resistance and gestational diabetes. There is no consensus on the definition of vitamin D deficiency, but most scientists define vitamin D deficiency as less than 20 ng/mL (50 nmoL/L) of 25-hydroxyvitamin D. Vitamin D deficiency is common in women during pregnancy. Vitamin D can regulate the course of gestational diabetes, which may be related to regulation of insulin gene transcription, insulin secretion, intracellular and cytosolic calcium balance, inhibition of oxidative stress and inflammatory responses and alteration of glucose metabolism. This is a review article that aims to analyze the possible mechanism of vitamin D regulation of GDM, which provides a theoretical basis for clinical researchers in the future management of patients with GDM.

Background: Evolving evidence suggests both protein consumption and particulate matter less than 2.5 micrometers (PM2.5) might be related to ovarian cancer (OC) mortality. However, no epidemiological studies have explored their potential interaction. Objective: The objective of this study was to explore the association of dietary protein, PM2.5, and their interaction with the survival of OC patients. Methods: A prospective cohort study was carried out, which encompassed 658 newly diagnosed OC patients (18–79 years) residing in China. Dietary protein intakes were collected through a food frequency questionnaire examination, including total protein and protein from diverse sources. Average residential PM2.5 concentrations were evaluated using satellite-derived models. We calculated the hazard ratio (HR) and its 95 % confidence interval (CI) by adjusting for multiple variables using Cox proportional risk models. By assessing the relative excess risk due to interaction (RERI) arising from the interplay between PM2.5 exposure and dietary protein intake, we explored the additive interaction between the two. Multiplicative interaction was assessed through a cross-product interaction term. Results: During a median follow-up of 37.60 months, 123 deaths were documented. As for all-cause mortality, the multivariate-adjusted HRs (95 % CIs) in the highest vs. the lowest tertile were 0.57 (0.35–0.93), 0.60 (0.36–0.99), and 0.58 (0.37–0.90) for intakes of fish, egg, as well as fruit/vegetable protein, respectively (all P for trend < 0.05). A positive association between PM2.5 exposure and all-cause mortality was observed (HR=1.52; 95 % CI: 1.13–2.05, per interquartile range increment). Notably, dietary fish, egg, and fruit/vegetable protein modified these associations, as patients with lower intakes had significantly higher PM2.5-related mortality in the cohort (all P for interaction < 0.05). Conclusions: This study provides evidence linking the potential interactions between dietary fish, egg, and fruit/vegetable protein intake and PM2.5 exposure on all-cause mortality of OC patients. Our study demonstrates the importance of adherence to a certain protein diet in reducing PM2.5-related mortality risk for OC patients.

Background: Although evidence suggests that perfluoroalkyl and polyfluoroalkyl substances (PFASs) are positively correlated to several disease risks, no studies have proven if plasma PFASs are related to ovarian cancer survival. Objective: To explore the association between plasma PFASs and high-grade serous ovarian cancer (HGSOC) overall survival (OS) in the population who did not smoke. Methods: We conducted a nested case-control study within the Ovarian Cancer Follow-Up Study, matching 159 dead patients and 159 survival ones based on body mass index, sample date, and age at diagnosis. Nine plasma PFASs were extracted by solid phase extraction and measured using a liquid chromatography system coupled with tandem mass spectrometry. Baseline plasma concentrations of perfluorinated carboxylic acids (PFCAs) [perfluorooctanoic acid (PFOA), perfluorononanoic acid (PFNA), perfluorodecanoic acid (PFDA), and perfluoroheptanoic acid (PFHpA)] and perfluorinated sulfonic acids (PFSAs) [perfluorooctane sulfonic acid (PFOS) and perfluorohexane sulfonic acid (PFHxS)] were calculated. Odds ratios (ORs) and corresponding 95 % confidence intervals (CIs) were calculated via conditional logistic regression models. To elucidate the combined effects, Bayesian kernel machine (BKMR), and regression quantile g-computation (QGC) models were utilized. Result: In full-adjusted model, significant differences were observed between HGSOC survival and perfluorobutane sulfonic acid, PFHpA, PFHxS, PFOS, PFCA, and PFSA. ORs and 95 %CIs were 2.74 (1.41–5.31), 1.97 (1.03–3.76), 2.13 (1.15–3.95), 2.28 (1.16–4.47), 3.74 (1.78–7.85), and 2.56 (1.31–5.01), respectively for the highest tertile compared with the lowest tertile. The QGC and BKMR models indicated that elevated concentrations of PFAS mixtures were associated with poor OS in HGSOC. Conclusions: Both individual and mixed plasma PFASs may relate to poor OS of HGSOC. Further research is necessary to establish causality, and it is recommended to reinforce environmental risk mitigation strategies to minimize PFAS exposure.

Avian pathogenic Escherichia coli (APEC) is a major threat to the poultry industry, causing bloodstream and extraintestinal infections. Type II toxin-antitoxin (TA) systems are known to aid bacterial pathogens in adapting to stress, promoting persister cell formation, and enhancing virulence. While type II TA systems have been extensively studied in many pathogens, APEC-derived TAs have received limited attention. Our study focused on the YafN-YafO type II TA system in APEC O2 strain E058. Using bacterial two-hybrid and pull-down assays, we confirmed the interaction between YafN and YafO. Electrophoretic mobility shift assays (EMSA) and lacZ fusion reporter assays demonstrated that YafN negatively autoregulates its own operon. The deletion of yafNO resulted in a significant reduction in persister cell formation under antibiotic and environmental stress (P < 0.01). Moreover, the yafNO mutant showed a ∼3-fold reduction in survival within chicken macrophages and attenuated virulence in chicken infection models, with a 44-fold increase in LD50 and ∼80-fold reduction in bacterial loads in blood and tissues (P < 0.01). These results demonstrate that the YafN-YafO is an active type II TA system in APEC E058, contributing to both stress resistance and virulence. Targeting this system could offer a novel strategy for controlling APEC infections.

Summary: Background: Ovarian cancer (OC) is a heterogeneous malignancy with multiple histological subtypes, showing global variability in incidence. Temporal changes in diagnostic criteria and risk factors might influence the incidence and distribution of OC and its subtypes. Methods: This study analyzed incidence patterns (2013–2017) and trends (1988–1992 to 2013–2017) of OC and its subtypes across 65 and 40 countries, respectively. Data were extracted from the Cancer Incidence in Five Continents (CI5 Ⅻ) and CI5plus databases (accessed in June 2024). Annual percent changes were computed to describe trends in age-standardized rates (ASRs) of OC and its subtypes. Proportions of ASR for each subtype relative to the ASR of OC for individual countries were calculated. Findings: The incidence of OC displayed marked disparities across regions and Human Development Index (HDI), with the highest ASRs in Eastern and Central Europe and very high HDI regions, and the lowest in Africa, Asia, and medium HDI regions. Despite stable trend in ASRs of OC globally, notable declines were observed in Europe, America, and Oceania, in contrast to increases in Asian countries like Japan and South Korea. Globally, serous carcinomas remained the most prevalent subtype. European countries exhibited a higher proportion of serous carcinomas, while Asian countries had a higher proportion of endometrioid and clear cell carcinomas. Although trends in subtypes also remained stable, ASRs increased over time for serous carcinomas and germ cell tumor in most countries, while mucinous carcinomas and adenocarcinoma NOS showed a decline. Interpretation: Variations in global patterns and trends in OC incidence and its subtypes might be influenced by genetic and reproductive factors. Consequently, region-specific prevention strategies and ongoing surveillance are essential to mitigate the burden of OC. Funding: The National Key Research and Development Program of China (No.2022YFC2704205), the Natural Science Foundation of China (No.82073647, 82373674, and 82103914), Outstanding Scientific Fund of Shengjing Hospital, 345 Talent Project of Shengjing Hospital of China Medical University, the Max Planck – University of Helsinki Center from the Jane and Aatos Erkko Foundation (No.210046), the Max Planck Society (No.5714240218), the University of Helsinki (No.77204227), and the European Union (ERC Synergy, BIOSFER, 101071773).

Pharmacotherapy is crucial for advanced hepatocellular carcinoma (HCC). The multi-kinase inhibitor donafenib offers superior survival benefits over sorafenib. Donafenib has first-line status, but there is limited research for combination therapies with this anticancer agent. This study aimed to delineate donafenib's antitumor effects, including transcriptomics and proteomics to characterize gene expression changes in donafenib-treated HCC cell lines. In vitro and in vivo tumorigenicity studies were conducted to evaluate the combined antitumor effects of donafenib. Proteomic and transcriptomic analyses identified that donafenib downregulated fatty acid desaturase 2 (FADS2) at the protein and mRNA levels. In vitro and in vivo assays revealed an inhibitory effect of FADS2 blockade on HCC cell malignancy. The combination of donafenib and the FADS2 inhibitor sc-26,196 produced synergistic antitumor action, enhancing therapeutic efficacy in HCC cell lines and xenografted tumors in nude mice. These findings highlight the potential of FADS2 as a biomarker for HCC and show a promising combinatorial therapy for its treatment. Thus, we provide a theoretical basis for translating laboratory research into clinical applications.

Luteolin is a kind of natural flavonoid, widely existing in a variety of plants, has been revealed to have a wide range of biological activities. In recent years, the research results of luteolin are abundant. Here we review the latest research results of luteolin in order to provide new ideas for further research and development of luteolin. In this paper, the focus of the search was published between 2010 and 2024 on the extraction and determination of luteolin, biological activities, and the development and application of luteolin products. A comprehensive search using the keyword ''luteolin'' was conducted in the PubMed, Web of Science and WIPO databases. Through the collection of related literature, this paper summarized a variety of extraction techniques of luteolin, including immersion extraction, solvent extraction, ultrasonic-assisted extraction, supercritical fluid extraction and so on. The determination methods include: thin layer chromatography (TLC), high performance liquid chromatography (HPLC), capillary electrophoresis (CE), electrochemical method (ED) and so on. In addition, the biological activities of luteolin, including antioxidant, anti-inflammatory, anti-tumor, antibacterial, analgesic and so on, were described. And luteolin as the main component of the product is being gradually developed, and has been used in the field of food, medicine and cosmetics. This paper provides a reference for further study of luteolin.

AbstractHypertension is a prevalent chronic condition worldwide that can impact patients’ quality of life. Oral antihypertensive drugs are widely used to manage high blood pressure, primarily by regulating the renin-angiotensin-aldosterone system. Nevertheless, limited efficacy and low compliance represent significant obstacles, arising primarily from dose, duration, and medication type restrictions. Furthermore, the prolonged use of antihypertensive medication may result in dependence and adverse effects, without any substantial improvement in achieving targeted blood pressure leves. As a result, research has focused on using exercise therapy to treat hypertension. Tai Chi, a widely-practiced Chinese health exercise, has evolved into a form of exercise therapy that might help alleviate the risk associated with hypertension. Therefore, this article aims to outline the role of Tai Chi in preventing and managing hypertension.

ABSTRACTConvex and concave hulls originating from computational geometry are widely applied in practice. For instance, to determine the boundaries of a geographical area within a group of cities, convex hulls can represent the approximate boundaries of the areas. Concave hulls can accurately describe the shape of the area. The traditional methods for solving two-dimensional convex hull problems include the Jarvis March algorithm and the Graham scanning algorithm. The K-nearest neighbours and alpha-shape methods are designed for solving the concave hull problem. Other than traditional algorithms, we consider using deep neural networks to handle the convex and concave hull problems. General neural networks cannot deal with the problem whose output is a variable-length sequence. Our study provides a machine-learning approach for solving the convex hull and concave hull problems. We combine the Pointer network (Ptr-Net) with the Transformer model and propose the DeepHullNet. The trained DeepHullNet can provide a feasible solution in the majority of cases. The experimental results show that DeepHullNet outperforms the original Ptr-Net regarding accuracy. Compared with traditional methods, DeepHullNet can generate a good solution quickly, and the running time is shortened by nearly 100 times based on GPU.

Timely and accurate mapping of paddy rice cultivation based on remote sensing technology is crucial and valuable for ensuring food security and sustainable environmental management. In most relevant studies, rice mapping was conducted using time-series images, but conventional rice mapping methods are not specifically designed for time-series data, making it difficult to extract the deep information contained in these data. To address these problems, in this paper, an automatic rice mapping method based on an integrated time-series gradient boosting tree (Auto-ITSGBT) is proposed using GF-6 WFV and Sentinel-2 MSI data. This method accounts for the local and overall shape features of time-series curves, and fully exploits the information related to phenological characteristics between time-series data. The proposed rice mapping method is tested and validated in three typical rice-producing areas, which are located in different provinces of China characterized by diverse climate conditions, planting times or topographies. The results show that the overall accuracy and Kappa coefficient of the method exceeded 95% and 0.93, respectively, at all study sites, respectively. Our method performs better than the existing competing methods, with an overall accuracy improvement of 2% to 4%. To identify the rice planting areas as early as possible, rice mapping was conducted by reducing the number of images one by one. The rice distribution map was obtained in mid-July with an overall accuracy of at least 90%, thus obtaining a spatial distribution map of rice with high accuracy before harvesting.

Hyperuricaemia (HUA) is an abnormally high concentration of serum urate caused by either an excess of uric acid production or decreased excretion capacity in the body. Serum urate concentration forms sodium salts that deposit in the soft tissues of the joints, ultimately leading to gout. Additionally, HUA is strongly associated with several acute and chronic illnesses. In various clinical guidelines and practices, xanthine oxidase inhibitors, such as allopurinol and febuxostat, are commonly used as the initial medication for treating HUA. However, extended usage of urate-lowering drugs may have risks, including cardiovascular thrombotic events and hepatic impairment. Implementing a scientifically informed fitness diet in conjunction with appropriate exercise may decrease HUA. Unfortunately, there is currently a shortfall in exercise intervention trials for individuals suffering from HUA. Most of the previous evidence suggesting that exercise improves serum urate levels comes from intervention trials in other populations, and serum urate is only one of the outcomes observed. This opinion article analyses the causes of HUA, offers dietary and exercise guidance with the aim of furnishing a point of reference for individuals with HUA or fitness enthusiasts.

Mining latent information from human trajectories for understanding our cities has been persistent endeavors in urban studies and spatial information science. Many previous studies relied on manually crafted features and followed a supervised learning pipeline for a particular task, e.g. land use classification. However, such methods often overlook some types of latent information and the commonalities between varying urban sensing tasks, making the features engineered for one specific task sometimes not useful in other tasks. To tackle the limitations, we propose a multi-view trajectory embedding (MTE) approach to learn the features of urban regions (region representations) in an unsupervised manner, which does not rely on a specific task and thus can be generalized to varying urban sensing tasks. Specifically, MTE incorporates three salient information views carried by human trajectories, i.e. transition, spatial, and temporal views. We utilize skip-gram to model human transition patterns exhibited from massive amounts of human trajectories, where long-range dependency is meaningful. Subsequently, we leverage unsupervised graph representation learning to model spatial adjacency and temporal pattern similarities, where short-range dependency is favorable. We perform extensive experiments on three downstream tasks, i.e. land use classification, population density estimation, and house price prediction. The results indicate that MTE considerably outperforms a series of competitive baselines in all three tasks, and different information views have varying levels of effectiveness in particular downstream tasks, e.g. the temporal view is more effective than the spatial view in land use classification, while it is the opposite in house price prediction.

Recycled aggregate concrete is a promising low carbon material, which need further analysis on the durability. To investigate the influence of sulfate erosion on recycled concrete made with high-belite sulfoaluminate cement (HBCSA), this study utilized compressive strength and microhardness test to evaluate the effect of sulfate on ITZ. Then by using backscattered electron imaging, scanning electron microscope and energy spectrometry, the mechanism for the microstructural changes that occurred before and after sulfate erosion is revealed. Results showed that after 60 days of sulfate erosion, both aggregate-new mortar and new–old mortar interfaces display reduced microhardness and widened transition zones. Specifically, in the C30 group post-erosion, the microhardness values for the aggregate-new mortar interface ranged from 50.3 to 66.9 MPa, while the new–old mortar interface exhibited a range of 47–77 MPa. Besides, the new–old mortar interface exhibit marginally superior sulfate resistance to the aggregate–new mortar interface at the same concrete strength grade. Moreover, sulfate resistance improvs across all interfaces with increasing strength class. For instance, in the aggregate-new mortar interface, the maximum microhardness post-erosion for C40 showed a 51.6 % increase compared to C30. Through microstructure analysis, it is found that after sulfate erosion, the aggregate–new mortar and new–old mortar interfaces of HBCSA recycled concrete are both enriched with abundant ettringite and gypsum, which causes considerable swelling erosive product formation and even cracking. The less formed cracks in new–old mortar interfaces results in the better sulfate resistance. The finding is helpful for the future research on the high sulfate resistant recycled aggregate concrete.

Abstract Pseudorabies have caused enormous economic losses in China’s pig industry and have recurred on many large pig farms since late 2011. The disease is caused by highly pathogenic, antigenic variant pseudorabies virus (vPRV) strains. Our laboratory isolated a pseudorabies virus in 2015 and named it XJ5. The pathogenic ability of this mutant strain was much stronger than that of the original isolate. After we sequenced its whole genome (GenBank accession number: OP512542), we found that its overall structure was not greatly changed compared with that of the previous strain Ea (KX423960.1). The whole genome alignment showed that XJ5 had a strong genetic relationship with the strains isolated in China after 2012 reported in GenBank. Based on the isolation time of XJ5 and the mutation and recombination analysis of programs, we found that the whole genome homology of XJ5 and other strains with Chinese isolates was greater than 95%, while the homology with strains outside Asia was less than 94%, which indicated that there may be some recombination and mutation patterns. We found that virulent PRV isolates emerged successively in China in 2011 and formed two different evolutionary clades from foreign isolates. At the same time, this may be due to improper immunization and the presence of wild strains in the field, and recent reports have confirmed that Bartha vaccine strains recombine with wild strains to obtain new pathogenic strains. We performed genetic evolution analysis of XJ5 isolated and sequenced in our laboratory to trace its possible mutations and recombination. We found that XJ5 may be the result of natural mutation of a virus in a branch of mutant strains widely existing in China.

Abstract Mitochondrial RNA (mtRNA) in the cytosol can trigger the innate immune sensor MDA5, and autoinflammatory disease due to type I IFN. Here, we show that a dominant negative mutation in the gene encoding the mitochondrial exonuclease REXO2 may cause interferonopathy by triggering the MDA5 pathway. A patient characterized by this heterozygous de novo mutation (p.T132A) presented with persistent skin rash featuring hyperkeratosis, parakeratosis and acanthosis, with infiltration of lymphocytes and eosinophils around small blood vessels. In addition, circulating IgE levels and inflammatory cytokines, including IFNα, are found consistently elevated. Transcriptional analysis highlights a type I IFN gene signature in PBMC. Mechanistically, REXO2 (T132A) lacks the ability to cleave RNA and inhibits the activity of wild-type REXO2. This leads to an accumulation of mitochondrial dsRNA in the cytosol, which is recognized by MDA5, leading to the associated type I IFN gene signature. These results demonstrate that in the absence of appropriate regulation by REXO2, aberrant cellular nucleic acids may accumulate and continuously trigger innate sensors, resulting in an inborn error of immunity.

Abstract A dynamic nonline-of-sight (NLOS) angle discrimination method is proposed to address the insufficiency of current research on the NLOS error characteristics of ultrawideband (UWB) signals in dynamic environments as well as the problem that UWB signals frequently suffer from occlusion, leading to poor or impossible localization. The experimental results indicate that the degree of UWB signal occlusion increases as the horizontal angle decreases, and when the horizontal angle is less than 167°, the UWB ranging error is so large that no ranging value is available. On this basis, a tightly integrated UWB/MEMS IMU positioning algorithm incorporating NLOS angle discrimination and map constraints is proposed; it employs horizontal angles to discriminate UWB ranging values in NLOS environments in accordance with the dynamic NLOS characteristics of UWB signals to assign better weights to UWB observations. Through comparative analysis of the results from both groups of experiments, the algorithm achieved northward, eastward, and planar positioning errors of 0.189 m and 0.126 m, 0.119 m and 0.134 m, 0.243 m and 0.211 m, respectively. Compared to the Robust Adaptive Kalman Filtering algorithm, the positional accuracy in the plane improved by 22.9% and 28.5%, respectively.

Abstract Background Early-stage breast cancer (BC) presents a certain risk of recurrence, leading to variable prognoses and complicating individualized management. Yet, preoperative noninvasive tools for accurate prediction of disease-free survival (DFS) are lacking. This study assessed the potential of strain elastography (SE) and diffuse optical tomography (DOT) for non-invasive preoperative prediction of recurrence in T1 BC and developed a prediction model for estimating the probability of DFS. Methods A total of 565 eligible patients with T1 invasive BC were enrolled prospectively and followed to investigate the recurrence. The associations between imaging features and DFS were evaluated and a best-prediction model for DFS was developed and validated. Results During the median follow-up period of 10.8 years, 77 patients (13.6%) developed recurrences. The fully adjusted Cox proportional hazards model showed a significant trend between an increasing strain ratio (SR) (P

Abstract Objective To investigate pantothenate kinases 1 (PANK1) expression in kidney renal clear cell carcinoma (KIRC) tissues, analyze its correlation with clinicopathological features and prognosis, and explore its impact on invasion, migration, and apoptosis in KIRC cells. Methods GEPIA (gene expression profiling interactive analysis), UALCAN and LinkedOmics, were employed to analyze PANK1 expression in KIRC tissues and its correlation with clinical characteristics. Comparative analyses were performed between KIRC (Caki-1 and 786-O) and noncancerous renal cells (HK-2 and RPTEC). Transfection with PANK1 activation particles was conducted, followed by Wound healing, Transwell assay, Annexin V-fluorescein isothiocyanate/propidium iodide (Annexin V-FITC/PI) staining, quantitative reverse-transcription polymerase chain reaction (qRT-PCR), and Western blotting. Results PANK1 was down-regulated in KIRC tissues and cells compared to normal tissues and noncancerous cells. Correlation analyses linked PANK1 expression with clinicopathological features in KIRC, with high PANK1 expression associated with a favorable outcome. High PANK1 expression correlated positively with E-cadherin (CDH1), tight junction protein 1 (TJP1), Fas cell surface death receptor (FAS), caspase-8 (CASP8), and CASP9, while showing a negative correlation with vimentin (VIM), snail family transcriptional repressor 1 (SNAIL1), twist family BHLH transcription factor 1 (TWIST1), and TWIST2. PANK1 overexpression increased CDH1, TJP1, FAS, CASP8, and CASP9 while downregulating SNAIL1, VIM, TWIST1, and TWIST2, inhibiting invasion and migration, and promoting apoptosis in KIRC cells. Conclusion PANK1 down-regulation in KIRC tissues correlated with clinicopathological features and prognosis. Its overexpression modulated epithelial-mesenchymal transition (EMT)-related gene, inhibited invasion, promoted apoptosis in KIRC cells, highlighting its role in disease progression and therapeutic potential.

Digital twins and the physical assets of electric power systems face the potential risk of data loss and monitoring failures owing to catastrophic events, causing surveillance and energy loss. This study aims to refine maintenance strategies for the monitoring of an electric power digital twin system post disasters. Initially, the research delineates the physical electric power system along with its digital counterpart and post-disaster restoration processes. Subsequently, it delves into communication and data processing mechanisms, specifically focusing on central data processing (CDP), communication routers (CRs), and phasor measurement units (PMUs), to re-establish an equipment recovery model based on these data transmission methodologies. Furthermore, it introduces a mathematical optimization model designed to enhance the digital twin system’s post-disaster monitoring efficacy by employing the branch-and-bound method for its resolution. The efficacy of the proposed model was corroborated by analyzing an IEEE-14 system. The findings suggest that the proposed branch- and-bound algorithm significantly augments the observational capabilities of a power system with limited resources, thereby bolstering its stability and emergency response mechanisms.

Remanufacturing is regarded as a sustainable manufacturing paradigm of energy conservation and environment protection. To improve the efficiency of the remanufacturing process, this work investigates an integrated scheduling problem for disassembly and reprocessing in a remanufacturing process, where product structures and uncertainty are taken into account. First, a stochastic programming model is developed to minimize the maximum completion time (makespan). Second, a Q-learning based hybrid meta-heuristic (Q-HMH) is specially devised. In each iteration, a Q-learning method is employed to adaptively choose a premium algorithm from four candidate ones, including genetic algorithm (GA), artificial bee colony (ABC), shuffled frog-leaping algorithm (SFLA), and simulated annealing (SA) methods. At last, simulation experiments are carried out by using sixteen instances with different scales, and three state-of-the-art algorithms in literature and an exact solver CPLEX are chosen for comparisons. By analyzing the results with the average relative percentage deviation (RPD) metric, we find that Q-HMH outperforms its rivals by 9.79%−26.76%. The results and comparisons verify the excellent competitiveness of Q-HMH for solving the concerned problems.

The trans-medium water entry process of vehicles is often accompanied by multiphase flow, cavitation, phase change, and turbulence instability, which not only heighten the complexity of the flow field, but also render the forces highly unsteady and nonlinear. A numerical model for the water entry process of vehicles was developed. The volume of fluid(VOF) model was employed to capture the gas-liquid interface, and the Schnerr-Sauer model was utilized to describe the cavitation that occurred during the trans-medium process. The simulation of the water entry process of the trans-medium vehicle under different ventilation flows and deflection angles of the cavitator was carried out to investigate the flow field and cavity evolution laws during the trans-medium process. In addition, the fluid dynamics characteristics, as well as the kinematic characteristics of the vehicle during trans-medium process were analyzed. The simulation results show that the vehicle will present two different attitude change modes with the change of the ventilation flow during the water entry process: the increasing angular velocity leveling mode and the periodical pitching-type leveling mode. The water entry leveling process of the vehicle in different modes will show different motion characteristics. Moreover, an increase in the deflection angle of the cavitator and a decrease in the ventilation flow can improve the attitude change rate of the vehicle during the trans-medium water entry process.

The water exit process of vehicles is very complicated, accompanied by multiphase flow, cavitation, phase transition, and turbulence instability, and the applied force is highly unsteady and nonlinear. At present, studies on the water exit problem of the vehicle with cavitation focus on the vertical or oblique water exit, emphasizing the trajectory and attitude of the vehicle. There are few studies on the water exit process of the supercavitating vehicle. In this paper, based on STAR-CCM+ software, overlapping grid technology was used for meshing, and the volume of fluid(VOF) model was used to capture the gas-liquid interface. The Schnerr-Sauer model described the cavitation process around the vehicle, and a numerical calculation model of the water exit process of the vehicle was established. The water exit process of the vehicle under different sailing conditions(initial velocity, initial water depth, and ventilation) was simulated and calculated, and the flow field and cavity evolution laws under different conditions were obtained. The hydrodynamic and kinematic characteristics of the supercavitating vehicle were analyzed. The simulation results show that the underwater motion of the vehicle with different initial velocities presents two different modes. Under different water depths, the initial cavity number is different. Cavity around the vehicle is more likely to rupture in deeper waters. The cavity morphology can be improved effectively by increasing the ventilation.

In order to study the underwater trajectory and related dynamics characteristics of trans-medium vehicles, a trans-medium vehicle was used as the research object. The dynamics equations were established based on the momentum theorem and the moment of momentum theorem, and the dynamics characteristics of the trans-medium vehicle at different velocities and cavitator’s angles were analyzed. The results show that increasing the initial velocity will slightly reduce the horizontal navigation distance and navigation depth of the vehicle, and the velocity will decrease faster; increasing the cavitator’s angle will also lead to a slight decrease in the horizontal navigation distance and navigation depth of the vehicle. Reducing the initial angle has a significant impact on the horizontal navigation distance of the vehicle and the angle at the end of the calculation, but it almost does not affect the acceleration and force characteristics.

Background: Environmental pollution has emerged as a significant determinant in ovarian cancer prognosis. However, limited evidence exists regarding the correlations between heavy metals and ovarian cancer prognosis. Objective: To elucidate the relationship between urinary heavy metals and their mixtures with overall survival (OS) of advanced high-grade serous ovarian cancer (HGSOC). Methods: Within the Ovarian Cancer Follow-Up Study, we conducted a nested case-control study. A sum of 159 deceased patients and an equal number of alive patients were included, matched by sample date, body mass index, and age at diagnosis. Urinary concentrations of five heavy metals were quantified: arsenic (As), cadmium (Cd), chromium (Cr), mercury (Hg), and lead (Pb). Conditional logistic regression models were employed to calculate odds ratios (ORs) and their 95 % confidence intervals (CIs). To elucidate joint effects, we utilized quantile g-computation and Bayesian kernel machine regression models. Results: For the multivariable adjusted conditional logistic regression model, significant associations were found between high urinary levels of As (OR=1.99, 95 %CI: 1.05–3.79), Cd (OR=2.56, 95 %CI: 1.29–5.05), Hg (OR=2.24, 95 %CI: 1.09–4.62), and Pb (OR=3.80, 95 %CI: 1.75–8.27) and worse OS of HGSOC, comparing the highest tertile to the lowest. Analysis of joint effects showed that elevated concentrations of heavy metal mixtures were related to poor OS of HGSOC. Pb exhibited the highest contribution to the overall association within the metal mixtures. Conclusions: High urinary heavy metal concentrations were linked to worse OS of HGSOC. Future research is necessary to validate our findings.

In the multi-robot swarm control algorithm, the traditional rigid formation algorithm has low formation redundancy, and it is difficult to flexibly adapt to the external environment. In this study, centroidal Voronoi tessellation (CVT) was used to control a group of robots for forming the required flexible formations and increasing the structural redundancy and internal carrying capacity of the multi-robot system. When the CVT area is divided in a non-convex environment, the Voronoi and non-convex areas will overlap, which will cause the robot to collide with the obstacles and hinder the optimization of the cost function. In this study, constrained CVT was used to solve the problem of region overlap in non-convex environments. The proposed path planning algorithm ensured the safe movement of the robot and explored the applicability of the algorithm in different scenarios. Finally, the performance of the algorithm in the non-convex area was verified and discussed by analyzing the simulation and experimental results for the convex and non-convex environments. The results showed that the constrained CVT could control the robot to generate the formation as quickly as possible in the non-convex area, and it was easy to dynamically switch the formation according to the external environment.

Avian pathogenic Escherichia coli (APEC) can spread beyond the intestines and cause systemic infections, leading to various clinical manifestations, including airsacculitis, pericarditis, perihepatitis and colisepticemia. The mechanisms facilitating this extraintestinal infections are not fully understood. In this study, we investigate how the tolA gene affects APEC virulence by encoding a protein involved in maintaining outer membrane integrity. We constructed a tolA deletion mutant of APEC strain E058 and evaluated its growth and survival in various environments, including in vitro cultures and in vivo infection models in chickens. We found that the motility-defective ΔtolA mutant exhibits reduced biofilm formation ability and weakened resistance to the environmental stresses, suggesting an important role for TolA in APEC's survival. The lack of tolA gene affects the bacterial ability to resist the host's immune system, such as complement-mediated serum killing or phagocytosis, as shown by the serum killing and macrophage phagocytosis assays. Additionally, in vivo infection studies using chickens demonstrated that the ΔtolA mutant displayed attenuated virulence, evidenced by reduced mortality and lower tissue bacterial burden. Reverse transcription quantitative real-time PCR (RT-qPCR) analysis revealed that inactivation of tolA led to downregulation of virulence genes associated with serum resistance (traT) and flagellar biosynthesis (fliR). Taken together, our findings demonstrate the multifaceted role of TolA protein in promoting the survival, immune evasion, biofilm formation, and virulence of APEC E058. This suggests that targeting TolA could potentially offer new strategies for combating APEC infections.

Background: Ambient air pollution might serve as a prognostic factor for ovarian cancer (OC) survival, yet the relationships between plant-based diet indices (PDIs) and OC survival remain unclear. We aimed to investigate the associations of comprehensive air pollution and PDIs with OC survival and explored the effects of air pollution-diet interactions. Methods: The present study encompassed 658 patients diagnosed with OC. The overall plant-based diet index (PDI), the healthful PDI (hPDI), and the unhealthful PDI (uPDI) were evaluated by a self-reported validated food frequency questionnaire. In addition, an air pollution score (APS) was formulated by summing the concentrations of particulate matter with a diameter of 2.5 microns or less, ozone, and nitrogen dioxide. Cox proportional hazard models were applied to calculate hazard ratios (HRs) and 95 % confidence intervals (CIs). The potential interactions of APS with PDIs in relation to overall survival (OS) were assessed on both multiplicative and additive scales. Results: Throughout a median follow-up of 37.60 (interquartile: 24.77–50.70) months, 123 deaths were confirmed. Comparing to the lowest tertiles, highest uPDI was associated with lower OS of OC (HR = 2.06, 95 % CI = 1.30, 3.28; P-trend

With the development of the pharmaceutical industry, halogenated hydrocarbons, which are the main raw materials and emissions of the pharmaceutical industry, may be defined as atmospheric emerging contaminants due to toxicity and low oxidation of the atmosphere. This study analyzed the volatile organic compounds (VOCs) emissions from four pharmaceutical companies located in the Yangtze River Delta. Samples were taken three times at each of the selected fixed and fugitive sampling sites in each company. Through testing, 141 VOCs were identified. The mean concentration and proportion of halogenated hydrocarbons from the four pharmaceutical companies were the highest of all the industries in the industrial park. They reached 18.9 ppm and 28.8 %, respectively. Fixed emissions of the companies exhibited the mean maximum concentration of dichloromethane and chlorobenzene, which are 11.4 ppm and 250.67 ppb. The mean concentration of fugitive emission of dichloromethane from the four companies in this study is lower than that of pharmaceutical companies in other studies. Newly detected halogenated hydrocarbons, such as 1,1-dichloropropanone and dichloronitromethane, present potential non-cancer and cancer risks to workers. Chlorobenzene was identified as a key potential cancer risk halogenated hydrocarbon the value of which reaches 0.00965. 2,6-dichloropyridine could be a potential emerging contaminant due to its lower MIR value and higher potential cancer risk. The study suggests that relevant pharmaceutical companies focus on the emissions of chlorobenzene and dichloromethane, which may be the atmospheric emerging contaminants for the pharmaceutical industry and focus on improve the treatment of waste gases in workshops and sewage stations.

Radiotherapy is a pivotal treatment for lung cancer, significantly impacting tumor control and patient quality of life. Despite its benefits, the molecular mechanisms underlying radiotherapy-induced biological alterations in lung cancer cells remain inadequately understood. In this study, we employed a mass spectrometry-based lipidomics approach to investigate lipid profile changes in a lung cancer mouse model post-radiation. Lewis lung carcinoma (LLC) cells were injected into C57BL/6J mice, followed by radiation treatment with varying split doses. Our results showed an increase in sterol lipids and a decrease in glycerolipids, specifically triacylglycerides, indicating disrupted lipid storage. Additionally, we observed significant changes in glycerophospholipid unsaturation, suggesting a remodeling of membrane properties that may influence cell survival. Linear regression analysis demonstrated a significant negative correlation between glycerophospholipid unsaturation index and tumor weight, indicating a potential role in radiation-induced tumor cell death. These findings provide new insights into the lipid metabolic pathways affected by radiotherapy and could inform the development of improved therapeutic strategies for lung cancer treatment.

The pathogenic nature of bacteria can be increased by cleaving antimicrobial peptides using omptins, to avoid or counter the host’s natural immune defenses. Plasmid-encoded OmpT (pOmpT or ArlC) in avian pathogenic Escherichia coli (APEC), like the chromosome-encoded OmpT (cOmpT), belongs to the omptin family and both exhibit highly similar sequences and structures. Through sequence alignment and physiological examinations, pOmpT has been identified as a virulence factor, distinct from cOmpT in terms of substrate specificity. When pOmpT is compared with cOmpT regarding their proteolytic activities and target substrates, Asp267 and Ser276 on loop 5 of cOmpT are found to be binding sites that facilitate substrate anchoring and enhance substrate cleavage (protamine or synthetic peptide) by the catalytic center. Conversely, the characteristics of residues at positions 267 and 276 on loop 5 of pOmpT inhibit protamine cleavage, yet allow the specific cleavage of the human antimicrobial peptide RNase 7, which plays a role in host defense. This finding suggests a relationship between these two binding sites and substrate specificity. Furthermore, the substrate-binding sites (residues 267 and 276, particularly residue 267) of cOmpT and pOmpT are determined to be critical in the virulence of APEC. In summary, residues 267 and 276 of pOmpT are crucial for the pathogenicity of APEC and offer new insights into the determinants of APEC virulence and the development of antimicrobial drugs.

Abstract A novel double side friction stir Z shape lap-butt welding (DS-FSZW) process was proposed to achieve excellent mechanical properties of Al/Cu medium-thick dissimilar joints. The influence of welding parameters on weld microstructure and properties of DS-FSZW joint were systematically investigated. It indicated that defect-free medium-thick Al/Cu DS-FSZW joint could be achieved under an optimal welding parameter. DS-FSZW joint was prone to form void defects in the bottom of the second-pass weld. The recrystallization mechanisms at the top and middle of the weld nugget zone (WNZ) were continuous dynamic recrystallization (CDRX) and geometric dynamic recrystallization (GDRX). While the major recrystallization mechanism at the bottom of the WNZ was GDRX. DS-FSZW joint of the optimal welding condition with 850 r/min-400 mm/min was produced with a continuous thin and crack-free IMCs layer at the Al/Cu interface, and the maximum tensile strength of this joint is 160.57 MPa, which is equivalent to 65.54% of pure Cu base material. Moreover, the corrosion resistance of Al/Cu DS-FSZW joints also achieved its maximum value at the optimal welding parameter of 850 r/min-400 mm/min. It demonstrates that the DS-FSZW process can simultaneously produce medium-thick Al/Cu joints with excellent mechanical performance and corrosion resistance.

Objective: Tumor cell malignancy is indicated by histopathological differentiation and cell proliferation. Ki-67, an indicator of cellular proliferation, has been used for tumor grading and classification in breast cancer and neuroendocrine tumors. However, its prognostic significance in pancreatic ductal adenocarcinoma (PDAC) remains uncertain. Methods: Patients who underwent radical pancreatectomy for PDAC were retrospectively enrolled, and relevant prognostic factors were examined. Grade of malignancy (GOM), a novel index based on histopathological differentiation and Ki-67, is proposed, and its clinical significance was evaluated. Results: The optimal threshold for Ki-67 was determined to be 30%. Patients with a Ki-67 expression level > 30% rather than ≤ 30% had significantly shorter 5-year overall survival (OS) and recurrence-free survival (RFS). In multivariate analysis, both histopathological differentiation and Ki-67 were identified as independent prognostic factors for OS and RFS. The GOM was used to independently stratify OS and RFS into 3 tiers, regardless of TNM stage and other established prognostic factors. The tumor-node-metastasis-GOM stage was used to stratify survival into 5 distinct tiers, and surpassed the predictive performance of TNM stage for OS and RFS. Conclusions: Ki-67 is a valuable prognostic indicator for PDAC. Inclusion of the GOM in the TNM staging system may potentially enhance prognostic accuracy for PDAC.