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BackgroundNitrogen dioxide (NO2) is one of the main air pollutants, and though China's NO2 pollution has been improving year by year, it maintains at a high level, threatening the health of the population. ObjectiveTo investigate the effect of short-term exposure to atmospheric NO2 on the coagulation indexes in obese and normal-weight young individuals and potential modification effect of temperature. MethodsBased on a parallel control panel study design, this study recruited 53 normal-weight and 44 obese young individuals. Three prospective follow-ups were conducted. Air pollution data were obtained from the fixed monitoring station closest to the participant's residences, and personal air pollution exposure was simulated based on time-activity log and infiltration factor for the week before every follow-up. Temperature was collected from China Meteorological Data Service Center. Venous blood samples were taken to measure platelet (PLT) count, mean platelet volume (MPV), soluble CD40 ligand (sCD40L), soluble P-selectin (sP-selectin), platelet aggregation rate (PAgT), and plasminogen activator inhibitor type-1 (PAI-1) during every follow-up. A linear mixed-effect model was used to assess the association between short-term atmospheric NO2 exposure and the coagulation indexes of weight grouped young individuals, and a stratified analysis was used to explore potential modification effect of temperature. ResultsThe median [interquartile range (IQR)] of personal atmospheric NO2 exposure concentrations was 21.47 (8.01) µg·m−3. Short-term exposure to atmospheric NO2 was significantly associated the increase of sCD40L and PAgT in the obese individuals, while the most significant association appeared at 5 d lag, and for each IQR increase in the average sliding exposure concentration of atmospheric NO2 with a 5 d lag, sCD40L increased by 27.4% (95%CI: 4.2%, 56.6%) and PAgT increased by 37.5% (95%CI: 12.2%, 68.6%); short-term exposure to atmospheric NO2 was significantly associated with the decrease of PLT and PAgT in the normal-weight individuals, while the most significant association appeared at 5 d lag or 7 d lag, and for each IQR increase in the average sliding exposure concentration of atmospheric NO2 with a 5 d lag, PLT decreased by 11.8% (95%CI: −17.8%, −5.3%), and for each IQR increase in the average sliding exposure concentration of atmospheric NO2 with a 7 d lag, PAgT decreased by 16.8% (95%CI: −30.6%, −0.4%). We didn't find statistically significant association of short-term exposure to atmospheric NO2 with PLT in the obese individuals or sCD40L in the normal-weight individuals, nor statistically significant association between short-term exposure to atmospheric NO2 and PAI-1, MPV, and sP-selectin in different weight grouped individuals. The stratified analysis found that short-term exposure to atmospheric NO2 was significantly associated with PAgT in the normal-weight individuals, or with PLT, sCD40L, and sP-selectin in the obese individuals only at high temperature. ConclusionsShort-term exposure to atmospheric NO2 has adverse effects on the coagulation indexes of different weight grouped young individuals, and the obese individuals are more sensitive to it than the normal-weight individuals. High temperature can enhance the adverse health effect of short-term exposure to atmospheric NO2.

There have been 2,585 county-level converged media centers established in mainland China. Enhancing the attractiveness of information published on WeChat official accounts to users is a major challenge faced by these centers. This research selected articles published by WeChat official accounts of five representative county-level media converged centers in the Guangxi Zhuang Autonomous Region (from June to October 2023, totaling 4045 WeChat articles). The negative binomial regression method was used to explore the impact of title features (including punctuations, Arabic numerals, internet slang, and emotions) on the readership of WeChat articles. The results indicate that title length, square brackets, dashes, book title marks, and vertical bars are negatively correlated with readership. Titles containing Arabic numerals and reader addressing correlate positively with readership. Positive emotion tones have a positive impact on the reading behavior of users, but the effects of different emotions are complex. This research offers valuable insights for the design of WeChat article titles at county-level converged media centers and provides a new case study for research into the title features of WeChat official accounts.

Penthiopyrad (PO), a succinate dehydrogenase inhibitor (SDHI) fungicide, poses a potential risk to fish. Here, we investigated the adverse effects of PO on endocrine regulation and reproductive capacity in zebrafish during a 21-d sublethal exposure to PO concentrations ranging from 0.02 to 2.00 mg/L. Following exposure to PO (0.20 and 2.00 mg/L), female-specific effects including follicle necrosis, structural disturbance of the yolk follicle, fusion of cortical follicles appeared in ovarian tissue of adult females, which led to a significant reduction in fertility. Correspondingly, 0.20 and 2.00 mg/L PO led to a marked reduction in the GSI values of females, and 2.00 mg/L PO caused a 31% decline in the proportion of perinucleolar oocytes (PCO) in oocytes. In addition, testosterone (T) level was obviously suppressed and 17β-estradiol (E2) level was increased in females after exposure to 2.00 mg/L PO. Male zebrafish treated with 0.20 and 2.00 mg/L of PO exhibited significant interstitial enlargement, edema in the testes, and reduced diameter of seminiferous tubules, along with a thinner basement membrane. The effects of PO on males were associated with significant increase in E2 level, suggesting that PO has an estrogenic effect on male fish. Greater E2 levels in serum were further supported by increased transcription levels of genes linked to the hypothalamic-pituitary-gonad-liver (HPGL) axis. Notably, transcription levels of cyp19a, er2b, era, and cyp19b was remarkably increased, exhibiting a clear link with variations in E2 levels. Overall, the present study demonstrates that PO induces reproductive impairment in zebrafish by promoting steroidogenesis.

Summary: Here, we present a protocol to generate a murine model of liver metastasis by directly injecting tumor cells into the portal vein under ultrasound guidance. We describe steps for animal and cell preparation and two techniques for injecting tumor cells. One technique is freehand, while the other technique is device-assisted using a 3D-printed prototype device. Finally, we describe tumor surveillance with bioluminescent imaging. : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Pansharpening techniques fuse the complementary information from panchromatic (PAN) and multispectral (MS) images to obtain a high-resolution MS image. However, the majority of existing pansharpening techniques suffer from spectral distortion owing to the low correlation between the MS and PAN images, and difficulties in obtaining appropriate injection gains. To address these issues, this article presents a novel pansharpening method based on the variational fractional-order geometry (VFOG) model and optimized injection gains. Specifically, to improve the correlation between the PAN and MS images, the VFOG model is constructed to generate a refined PAN image with a similar spatial structure to the MS image, while maintaining the gradient information of the original PAN image. Furthermore, to obtain accurate injection gains, and considering that the vegetated and nonvegetated regions should be dissimilar, an optimized adaptive injection gain based on the normalized differential vegetation index is designed. The final pansharpened image is obtained by an injection model using the refined PAN image and optimized injection gains. Extensive experiments on various satellite datasets demonstrate that the proposed method offers superior spectral and spatial fidelity compared to existing state-of-the-art algorithms.

Abstract Background The adverse effects of particulate air pollution on heart rate variability (HRV) have been reported. However, it remains unclear whether they differ by the weight status as well as between wake and sleep. Methods A repeated-measure study was conducted in 97 young adults in Beijing, China, and they were classified by body mass index (BMI) as normal-weight (BMI, 18.5–24.0 kg/m2) and obese (BMI ≥ 28.0 kg/m2) groups. Personal exposures to fine particulate matter (PM2.5) and black carbon (BC) were measured with portable exposure monitors, and the ambient PM2.5/BC concentrations were obtained from the fixed monitoring sites near the subjects’ residences. HRV and heart rate (HR) were monitored by 24-h Holter electrocardiography. The study period was divided into waking and sleeping hours according to time-activity diaries. Linear mixed-effects models were used to investigate the effects of PM2.5/BC on HRV and HR in both groups during wake and sleep. Results The effects of short-term exposure to PM2.5/BC on HRV were more pronounced among obese participants. In the normal-weight group, the positive association between personal PM2.5/BC exposure and high-frequency power (HF) as well as the ratio of low-frequency power to high-frequency power (LF/HF) was observed during wakefulness. In the obese group, personal PM2.5/BC exposure was negatively associated with HF but positively associated with LF/HF during wakefulness, whereas it was negatively correlated to total power and standard deviation of all NN intervals (SDNN) during sleep. An interquartile range (IQR) increase in BC at 2-h moving average was associated with 37.64% (95% confidence interval [CI]: 25.03, 51.51%) increases in LF/HF during wakefulness and associated with 6.28% (95% CI: − 17.26, 6.15%) decreases in SDNN during sleep in obese individuals, and the interaction terms between BC and obesity in LF/HF and SDNN were both statistically significant (p

Purine nucleoside phosphorylase (PNP) enables the breakdown and recycling of guanine nucleosides. PNP insufficiency in humans is paradoxically associated with both immunodeficiency and autoimmunity, but the mechanistic basis for these outcomes is incompletely understood. Here, we identify two immune lineage-dependent consequences of PNP inactivation dictated by distinct gene interactions. During T cell development, PNP inactivation is synthetically lethal with downregulation of the dNTP triphosphohydrolase SAMHD1. This interaction requires deoxycytidine kinase activity and is antagonized by microenvironmental deoxycytidine. In B lymphocytes and macrophages, PNP regulates Toll-like receptor 7 signaling by controlling the levels of its (deoxy)guanosine nucleoside ligands. Overriding this regulatory mechanism promotes germinal center formation in the absence of exogenous antigen and accelerates disease in a mouse model of autoimmunity. This work reveals that one purine metabolism gene protects against immunodeficiency and autoimmunity via independent mechanisms operating in distinct immune lineages and identifies PNP as a potentially novel metabolic immune checkpoint.

Summary: In traumatic brain injury (TBI), a diversity of brain resident and peripherally derived myeloid cells have the potential to worsen damage and/or to assist in healing. We define the heterogeneity of microglia and macrophage phenotypes during TBI in wild-type (WT) mice and Ccr2−/− mice, which lack macrophage influx following TBI and are resistant to brain damage. We use unbiased single-cell RNA sequencing methods to uncover 25 microglia, monocyte/macrophage, and dendritic cell subsets in acute TBI and normal brains. We find alterations in transcriptional profiles of microglia subsets in Ccr2−/− TBI mice compared to WT TBI mice indicating that infiltrating monocytes/macrophages influence microglia activation to promote a type I IFN response. Preclinical pharmacological blockade of hCCR2 after injury reduces expression of IFN-responsive gene, Irf7, and improves outcomes. These data extend our understanding of myeloid cell diversity and crosstalk in brain trauma and identify therapeutic targets in myeloid subsets.

As with the extensive use of complex software in many fields, such as finance, transportation, aeronautics, and astronautics, software plays an increasingly more important role in society. Software reliability becomes a critical bottleneck for system reliability and draws increasingly greater attention from software engineers. Many researchers find that traditional software verification and validation techniques are not sufficient to ensure complex software reliability, especially after being deployed. In this paper, therefore, we propose a novel software runtime monitoring method that can help with software runtime verification and software failure prediction. This method aims to monitor software execution trace that reveal the software runtime status. First, the framework of this method is proposed to introduce the entire process and two key problems. Second, an instrumentation method based on srcML, an open source tool used to extract the software abstract syntax tree, is presented. By this instrumentation technique, monitoring code can be inserted into source code and runtime data can be exported during the software execution process. Then, a runtime data-collection technique is proposed to collect runtime data exported by monitoring code. On one hand, the file stream mechanism is used to export data files that can be used to support offline analysis, while on the other hand a client-server structure is proposed to support online analysis. Finally, a case study on Nginx is used to show the feasibility of the proposed method.

Along with the development of remote sensing technology, the spatial–temporal variability of vegetation productivity has been well observed. However, the drivers controlling the variation in vegetation under various climate gradients remain poorly understood. Identifying and quantifying the independent effects of driving factors on a natural process is challenging. In this study, we adopted a potent machine learning (ML) model and an ML interpretation technique with high fidelity to disentangle the effects of climatic variables on the long-term averaged net primary productivity (NPP) across the Amazon rainforests. Specifically, the eXtreme Gradient Boosting (XGBoost) model was employed to model the Moderate-resolution Imaging Spectroradiometer (MODIS) NPP data, and the Shapley addictive explanation (SHAP) method was introduced to account for nonlinear relationships between variables identified by the model. Results showed that the dominant driver of NPP across the Amazon forests varied in different regions, with temperature dominating the most considerable portion of the ecoregion with a high importance score. In addition, light augmentation, increased CO2 concentration, and decreased precipitation positively contributed to Amazonia NPP. The wind speed for most vegetated areas was under the optimum, which benefits NPP, while sustained high wind speed would bring substantial NPP loss. We also found a non-monotonic response of Amazonia NPP to VPD and attributed this relationship to the moisture load in Amazon forests. Our application of the explainable machine learning framework to identify the underlying physical mechanism behind NPP could be a reference for identifying relationships between components in natural processes.

Cervical cancer (CESC) is a gynecologic malignant tumor associated with high incidence and mortality rates because of its distinctive management complexity. Herein, we characterized the molecular features of CESC based on the metabolic gene expression profile by establishing a novel classification system and a scoring system termed as METAscore. Integrative analysis was performed on human CESC samples from TCGA dataset. Unsupervised clustering of RNA sequencing data on 2,752 formerly described metabolic genes identified three METAclusters. These METAclusters for overall survival time, immune characteristics, metabolic features, transcriptome features, and immunotherapeutic effectiveness existed distinct differences. Then we analyzed 207 DEGs among the three METAclusters and as well identified three geneclusters. Correspondingly, these three geneclusters also differently expressed among the aforementioned features, supporting the reliability of the metabolism-relevant molecular classification. Finally METAscore was constructed which emerged as an independent prognostic biomarker, related to CESC transcriptome features, metabolic features, immune characteristics, and linked to the sensitivity of immunotherapy for individual patient. These findings depicted a new classification and a scoring system in CESC based on the metabolic pattern, thereby furthering the understanding of CESC genetic signatures and aiding in the prediction of the effectiveness to anticancer immunotherapies.

Multi-scale geometric analysis is a popular tool that is widely used in the field of multi-focus image fusion. It plays a large role in extracting the features from input images. In this paper, a novel multi-focus image fusion method based on a non-fixed-base dictionary and multi-measure optimization is presented in the non-subsampled shearlet transform (NSST) domain. The proposed approach contains the following four steps. The input images are first decomposed by NSST into low- and high-frequency coefficients. Second, a sparse representation (SR)-based framework is proposed and applied to merge the low-frequency coefficients of the input images. In this framework, a non-fixed-base dictionary iteratively trained by the previous dictionary is constructed, which represents the complex details of the source images. Third, a type-2 fuzzy logic scheme is introduced for the high-frequency coefficient fusion, which can effectively select the high-quality coefficients from the source images so that it can achieve better performance. Finally, an inverse NSST operation is conducted in the merged low- and high-pass subbands and thus obtains the initial fused image. A multi-measure optimization method is then employed to optimize the initial fused image, and thus, the final fused result is achieved. In this method, three different measures, namely, pixel difference, visual saliency, and similarity, are designed to select the focus regions more completely. The experimental results demonstrate that our proposed approach yields a better effect than other methods in both the visual quality and the objective assessment.

Current research on software vulnerability analysis mostly focus on source codes or executable programs. But these methods can only be applied after software is completely developed when source codes are available. This may lead to high costs and tremendous difficulties in software revision. On the other hand, as an important product of software design phase, architecture can depict not only the static structure of software, but also the information flow due to interaction of components. Architecture is crucial in determining the quality of software. As a result, by locating the architecture-level information flow that violates security policies, vulnerabilities can be found and fixed in the early phase of software development cycle when revision is easier with lower cost. In this paper, an approach for analyzing information flow vulnerability in software architecture is proposed. First, the concept of information flow vulnerability in software architecture is elaborated. Corresponding security policies are proposed. Then, a method for constructing service invocation diagrams based on graph theory is proposed, which can depict information flow in software architecture. Moreover, an algorithm for vulnerability determination is designed to locate architecture-level vulnerabilities. Finally, a case study is provided, which verifies the effectiveness and feasibility of the proposed methods.

An extending Borgonovo’s global sensitivity analysis is proposed to measure the influence of fuzzy distribution parameters on fuzzy failure probability by averaging the shift between the membership functions (MFs) of unconditional and conditional failure probability. The presented global sensitivity indices can reasonably reflect the influence of fuzzy-valued distribution parameters on the character of the failure probability, whereas solving the MFs of unconditional and conditional failure probability is time-consuming due to the involved multiple-loop sampling and optimization operators. To overcome the large computational cost, a single-loop simulation (SLS) is introduced to estimate the global sensitivity indices. By establishing a sampling probability density, only a set of samples of input variables are essential to evaluate the MFs of unconditional and conditional failure probability in the presented SLS method. Significance of the global sensitivity indices can be verified and demonstrated through several numerical and engineering examples.

INTRODUCTION: Pancreatic ductal adenocarcinoma (PDAC) is projected to rise to the second leading cause of U.S. cancer-related deaths by 2020. Novel therapeutic targets are desperately needed. MicroRNAs (miRs) are small noncoding RNAs that function by suppressing gene expression and are dysregulated in cancer. miR-21 is overexpressed in PDAC tumor cells (TC) and is associated with decreased survival, chemoresistance and invasion. Dysregulation of miR regulatory networks in PDAC tumor-associated fibroblasts (TAFs) have not been previously described. In this study, we show that miR-21 expression in TAFs promotes TC invasion. METHODS: In-situ hybridization for miR-21 was performed on the 153 PDAC patient UCLA tissue microarray and 23 patient-matched lymph node metastases. Stromal and TC histoscores were correlated with clinicopathologic parameters by univariate and multivariate Cox regression. miR-21 positive cells were further characterized by immunofluorescence for mesenchymal/epithelial markers. For in vitro studies, TAFs were isolated from freshly resected human PDAC tumors by the outgrowth method. miR-21 was overexpressed/inhibited in fibroblasts and then co-cultured with GFP-MiaPaCa TCs to assess TC invasion in modified Boyden chambers. RESULTS: miR-21 was upregulated in TAFs of 78% of tumors, and high miR-21 significantly correlated with decreased overall survival (P = 0.04). Stromal miR-21 expression was also significantly associated with lymph node invasion (P = 0.004), suggesting that it is driving TC spread. Co-immunofluorescence revealed that miR-21 colocalized with peritumoral fibroblasts expressing α-smooth muscle actin. Moreover, expression of miR-21 in primary TAFs correlated with miR-21 in TAFs from patient-matched LN metastases; evidence that PDAC tumor cells induce TAFs to express miR-21. miR-21 expression in TAFs and TCs promotes invasion of TCs and is inhibited with anti-miR-21. CONCLUSIONS: miR-21 expression in PDAC TAFs is associated with decreased overall survival and promotes TC invasion. Anti-miR-21 may represent a novel therapeutic strategy for dual targeting of both tumor and stroma in PDAC.

To efficiently evaluate the influence of the distribution parameters of the input variables on the failure probability of engineering structures and improve the reliability and safety of engineering structures in a targeted manner, new methods for the global reliability sensitivity analysis (RSA) of distribution parameters are proposed in this study based on the cubature formula (CF), surrogate sampling probability density function (SSPDF), and quasi-Monte Carlo (QMC) method. By introducing CF, the proposed methods can effectively improve the computational efficiency of the nested expectation and variance operators in the reliability sensitivity indices of the distribution parameters. Based on the concept of SSPDF, a surrogate importance sampling probability density function was developed. This not only overcomes the problem of the computational effort of propagating parameter uncertainty to the failure probability function (FPF), which depends on the dimensionality of the parameters; it also further improves the efficiency of the RSA of the parameters in the case of a small failure probability. Finally, by incorporating the idea of the QMC method, the process of calculating the reliability sensitivity indices of the parameters is reduced from a double-loop to a single-loop one. Three engineering examples are used in this study to demonstrate the efficiency and accuracy of the new algorithms. [ABSTRACT FROM AUTHOR]

Abstract Background Triple-negative breast cancer (TNBC) is highly heterogeneous, resulting in different responses to neoadjuvant chemotherapy (NAC) and prognoses among patients. This study sought to characterize the heterogeneity of TNBC on MRI and develop a radiogenomic model for predicting both pathological complete response (pCR) and prognosis. Materials and methods In this retrospective study, TNBC patients who underwent neoadjuvant chemotherapy at Fudan University Shanghai Cancer Center were enrolled as the radiomic development cohort (n = 315); among these patients, those whose genetic data were available were enrolled as the radiogenomic development cohort (n = 98). The study population of the two cohorts was randomly divided into a training set and a validation set at a ratio of 7:3. The external validation cohort (n = 77) included patients from the DUKE and I-SPY 1 databases. Spatial heterogeneity was characterized using features from the intratumoral subregions and peritumoral region. Hemodynamic heterogeneity was characterized by kinetic features from the tumor body. Three radiomics models were developed by logistic regression after selecting features. Model 1 included subregional and peritumoral features, Model 2 included kinetic features, and Model 3 integrated the features of Model 1 and Model 2. Two fusion models were developed by further integrating pathological and genomic features (PRM: pathology-radiomics model; GPRM: genomics-pathology-radiomics model). Model performance was assessed with the AUC and decision curve analysis. Prognostic implications were assessed with Kaplan‒Meier curves and multivariate Cox regression. Results Among the radiomic models, the multiregional model representing multiscale heterogeneity (Model 3) exhibited better pCR prediction, with AUCs of 0.87, 0.79, and 0.78 in the training, internal validation, and external validation sets, respectively. The GPRM showed the best performance for predicting pCR in the training (AUC = 0.97, P = 0.015) and validation sets (AUC = 0.93, P = 0.019). Model 3, PRM and GPRM could stratify patients by disease-free survival, and a predicted nonpCR was associated with poor prognosis (P = 0.034, 0.001 and 0.019, respectively). Conclusion Multiscale heterogeneity characterized by DCE-MRI could effectively predict the pCR and prognosis of TNBC patients. The radiogenomic model could serve as a valuable biomarker to improve the prediction performance.

Abstract Background and Aim The spatial distribution and interactions of cells in the tumor immune microenvironment (TIME) might be related to the different responses of triple‐negative breast cancer (TNBC) to immunomodulators. The potential of multiplex IHC (m‐IHC) in evaluating the TIME has been reported, but the efficacy is insufficient. We aimed to research whether m‐IHC results could be used to reflect the TIME, and thus to predict prognosis and complement the TNBC subtyping system. Methods The clinical, imaging, and prognosis data for 86 TNBC patients were retrospectively reviewed. CD3, CD4, CD8, Foxp3, PD‐L1, and Pan‐CK markers were stained by m‐IHC. Particular cell spatial distributions and interactions in the TIME were evaluated with the HALO multispectral analysis platform. Then, we calculated the prognostic value of components of the TIME and their correlations with TNBC transcriptomic subtypes and MRI radiomic features reflecting TNBC subtypes. Results The components of the TIME score were established by m‐IHC and demonstrated positive prognostic value for TNBC (p = 0.0047, 0.039,

Stringent response and quorum sensing (QS) are two essential mechanisms that control bacterial global metabolism for better survival. Sphingomonads are a clade of bacteria that survive successfully in diverse ecosystems. In silico survey indicated that 36 out of 79 investigated sphingomonads strains contained more than one luxI homolog, the gene responsible for the biosynthesis of QS signal acyl homoserine lactones (AHLs). Investigation of the regulatory effects of the stringent response gene rsh on QS related bioactivities were carried out using rsh mutants of Sphingobium japonicum UT26 and Sphingobium sp. SYK-6, both had three luxI homologs. Results indicated that deletion of rsh upregulated the overall production of AHLs and extracellular polymeric substances (EPS) in both UT26 and SYK-6 in rich medium, but affected expressions of these luxI/luxR homologs in different ways. In the poor medium (1% LB), rsh mutant of SYK-6 significantly lost AHLs production in broth cultivation but not in biofilm cultivation. The regulatory effects of rsh on QS activities were growth phase dependent in UT26 and culture condition dependent in SYK-6. Our results demonstrated the negative regulatory effect of rsh on QS activities in sphingomonads, which were very different from the positive effect found in sphingomonads containing only one luxI/R circuit. This study extends the current knowledge on the intricate networks between stringent response and QS system in sphingomonads, which would help to understand their survival advantage.

PurposeTo investigate the relationship between bone turnover markers (BTMs) and thyroid indicators in Graves’ disease (GD) and to further assess predictive value of changes in early stage retrospectively.MethodsWe studied 435 patients with GD and 113 healthy physical examiners retrospectively and followed up these two groups of patients after 6 months. We investigated the correlations between BTMs and other 15 observed factors, and analyzed the predictive value of FT3 and FT4 before and after treatment (FT3-P/FT3-A, FT4-P/FT4-A) on whether BTMs recovered.ResultsThe levels of thyroid hormones and BTMs in GD group were significantly higher than those in control group (P < 0.05) and decreased after 6 months of treatment. FT3, W, Ca and ALP were independent factors in predicting the elevation of OST. Duration of disease, FT3, TSH and ALP were independent factors in predicting the elevation of P1NP. Age, duration of disease, TRAb and ALP were independent factors in predicting the elevation of CTX-1. The AUC of FT3-P/FT3-A and FT4-P/FT4-A for predicting OST recovery were 0.748 and 0.705 (P < 0.05), respectively, and the cut-off values were 0.51 and 0.595. There was no predictive value for P1NP and CTX-1 recovery (P > 0.05).ConclusionBTMs were abnormally elevated in GD and were significantly correlated with serum levels of FT3, FT4, TRAb, Ca, and ALP. FT3 decreased more than 51% and FT4 dropped more than 59.5% after 6 months of treatment were independent predictors for the recovery of BTMs in GD.

Type I interferons (IFNs) are critical effectors of emerging cancer immunotherapies designed to activate pattern recognition receptors (PRRs). A challenge in the clinical translation of these agents is the lack of noninvasive pharmacodynamic biomarkers that indicate increased intratumoral IFN signaling following PRR activation. Positron emission tomography (PET) imaging enables the visualization of tissue metabolic activity, but whether IFN signaling-induced alterations in tumor cell metabolism can be detected using PET has not been investigated. We found that IFN signaling augments pancreatic ductal adenocarcinoma (PDAC) cell nucleotide metabolism via transcriptional induction of metabolism-associated genes including thymidine phosphorylase (TYMP). TYMP catalyzes the first step in the catabolism of thymidine, which competitively inhibits intratumoral accumulation of the nucleoside analog PET probe 3'-deoxy-3'-[18F]fluorothymidine ([18F]FLT). Accordingly, IFN treatment up-regulates cancer cell [18F]FLT uptake in the presence of thymidine, and this effect is dependent upon TYMP expression. In vivo, genetic activation of stimulator of interferon genes (STING), a PRR highly expressed in PDAC, enhances the [18F]FLT avidity of xenograft tumors. Additionally, small molecule STING agonists trigger IFN signaling-dependent TYMP expression in PDAC cells and increase tumor [18F]FLT uptake in vivo following systemic treatment. These findings indicate that [18F]FLT accumulation in tumors is sensitive to IFN signaling and that [18F]FLT PET may serve as a pharmacodynamic biomarker for STING agonist-based therapies in PDAC and possibly other malignancies characterized by elevated STING expression. [ABSTRACT FROM AUTHOR]

Antibiotics are considered as persistent emerging contaminants. The phenomenon of mixed exposure to the environment is a common occurrence causing serious harm to human health and the environment. Therefore, we employed enrofloxacin (ENR), chlortetracycline (CTC), methotrexate (TMP), chloramphenicol (CMP), and erythromycin (ETM) in this study. Nine treatments were designed using the uniform design concentration ratio (UDCR) method to systematically determine the toxicity of individual contaminants and their mixtures on Vibrio qinghaiensis sp.-Q67 through the time-dependent microplate toxicity assay. The combinatorial index (CI) method and the dose reduction index (DRI) were used to analyze the toxic interactions of the mixtures and the magnitude of the contribution of each component to the toxic interactions. The results showed that the toxicities of ENR, CTC, TMR, CMP, and ETM and their mixtures were time-dependent, with toxic effects being enhanced except when exposure time was prolonged. The types of toxic interactions in the ENR-CTC-TMR-CMP-ETM mixtures were found to be correlated with the proportion of each component’s concentration, where the proportion of the components exerted the most significant influence. Through DRI extrapolation, it was determined that the primary components of the mixture exhibited a pronounced dependency on time. Specifically, at the 4 h mark, TMP emerged as the predominant component, gradually giving way to ENR as time advanced. Upon analyzing the frequency of mixture interactions under specified effects, the additive effect appeared most frequently (66.6%), while the antagonist effect appeared the least frequently (15.9%) among the nine rays.

Emerging evidence suggests that intratumoral interferon (IFN) signaling can trigger targetable vulnerabilities. A hallmark of pancreatic ductal adenocarcinoma (PDAC) is its extensively reprogrammed metabolic network, in which nicotinamide adenine dinucleotide (NAD) and its reduced form, NADH, are critical cofactors. Here, we show that IFN signaling, present in a subset of PDAC tumors, substantially lowers NAD(H) levels through up-regulating the expression of NAD-consuming enzymes PARP9, PARP10, and PARP14. Their individual contributions to this mechanism in PDAC have not been previously delineated. Nicotinamide phosphoribosyltransferase (NAMPT) is the rate-limiting enzyme in the NAD salvage pathway, a dominant source of NAD in cancer cells. We found that IFN-induced NAD consumption increased dependence upon NAMPT for its role in recycling NAM to salvage NAD pools, thus sensitizing PDAC cells to pharmacologic NAMPT inhibition. Their combination decreased PDAC cell proliferation and invasion in vitro and suppressed orthotopic tumor growth and liver metastases in vivo. [ABSTRACT FROM AUTHOR]

Functional lysosomes mediate autophagy and macropinocytosis for nutrient acquisition. Pancreatic ductal adenocarcinoma (PDAC) tumors exhibit high basal lysosomal activity, and inhibition of lysosome function suppresses PDAC cell proliferation and tumor growth. However, the codependencies induced by lysosomal inhibition in PDAC have not been systematically explored. We performed a comprehensive pharmacological inhibition screen of the protein kinome and found that replication stress response (RSR) inhibitors were synthetically lethal with chloroquine (CQ) in PDAC cells. CQ treatment reduced de novo nucleotide biosynthesis and induced replication stress. We found that CQ treatment caused mitochondrial dysfunction and depletion of aspartate, an essential precursor for de novo nucleotide synthesis, as an underlying mechanism. Supplementation with aspartate partially rescued the phenotypes induced by CQ. The synergy of CQ and the RSR inhibitor VE-822 was comprehensively validated in both 2D and 3D cultures of PDAC cell lines, a heterotypic spheroid culture with cancer-associated fibroblasts, and in vivo xenograft and syngeneic PDAC mouse models. These results indicate a codependency on functional lysosomes and RSR in PDAC and support the translational potential of the combination of CQ and RSR inhibitors. [ABSTRACT FROM AUTHOR]

Background. Spontaneous preterm birth is one of the most common pregnancy complications in obstetric clinical practice, and its etiology is complex. The problems of low survival and high morbidity rates of premature infants need to be solved urgently. The platelet-to-lymphocyte ratio (PLR) and lymphocyte-to-monocyte ratio (LMR) are two novel biomarkers of inflammation, and several studies have linked PLR and LMR to spontaneous preterm birth. These systematic review and meta-analysis are aimed at analyzing the relationship between PLR and LMR in patients with spontaneous preterm birth to provide new ideas for the early prevention and treatment of spontaneous preterm births. Methods. Cochrane Library, EMBASE, PubMed, and China National Knowledge Infrastructure databases were inspected to gather PLR and LMR in patients with spontaneous preterm birth, all from the database to February 2022. Interstudy heterogeneity was evaluated using Cochran’s Q test and I2 statistic. Differences in PLR and LMR between patients with spontaneous preterm birth and full-term controls were evaluated by computing standardized mean differences and 95% confidence intervals. Publication bias and sensitivity analyses were also performed. Results. Nine studies were included in the meta-analysis based on the inclusion and exclusion criteria. The meta-analysis showed that serum PLR values were remarkably larger for patients with spontaneous preterm birth than for full-term controls (SMD=0.49, 95% CI: 0.13 to 0.84, P=0.007), whereas the difference between serum LMR in patients with spontaneous preterm birth and full-term controls was not statistically significant (SMD: 0.35, 95% CI: -0.18, 0.88, P=0.199). The results of Begg’s and Egger’s tests revealed that the publication bias of the meta-analysis was not significant. The outcomes of the sensitivity analysis showed that the individual studies did not influence the meta-analysis results. Conclusions. Current evidence shows that PLR is strongly associated with spontaneous preterm birth, whereas LMR is not. PLR has a certain clinical value in diagnosing and treating spontaneous preterm births, and our research will provide strong theoretical support for clinical work. In the future, it will be necessary to further explore the reasons for the increased PLR in the serum of patients with spontaneous preterm birth and other mechanisms inducing spontaneous preterm birth.

Background and objectivesThe glymphatic system is a recently discovered cerebrospinal fluid transport system and little is known about its dynamic changes after stroke. This study aimed to dynamically observe the structural and functional changes of the impaired glymphatic system in the thalamus after ischemic stroke by pathology and MRI.Materials and methodsIschemic stroke was induced by the middle cerebral artery occlusion (MCAO) model. A total of 20 Sprague-Dawley rats were randomly assigned into four groups: sham, MCAO 1 week, MCAO 2 week, and MCAO 2 month. All rats successively underwent neurological examination, dynamic contrast-enhanced MRI (DCE-MRI), and immunofluorescence staining. Immunofluorescence staining of glial fibrillary acidic protein (GFAP), aquaporin-4 (AQP4), ionized calcium-binding adaptor molecule 1 (Iba1), and beta-amyloid precursor protein (APP) were done in thalamus ventroposterior nucleus.ResultsThe astrocyte and microglial activation and the APP deposition in the MCAO 2 week group were the highest (P < 0.05 for all). The AQP4 polarization rates of the MCAO 2 week and 2 month groups were the lowest (P < 0.05 for all). Although there was no correlation between histological changes and MRI metrics in all four groups (P > 0.05 for all), the tendency of the APP deposition was nearly consistent with the one of the contrast agent retention in DCE-MRI.ConclusionThe glymphatic system in the thalamus was severely impaired at 2nd week after MCAO, and may be revealed by DCE-MRI. This study may provide a relevant theoretical basis for making a thorough inquiry of the mechanism of brain injury after stroke and clinical treatment of ischemic stroke and help readers appreciate the importance of DCE-MRI.

BackgroundIschemic stroke is one of the leading causes of human death and disability. Brain edema and peri-infarct astrocyte reactivity are crucial pathological changes, both involving aquaporin-4 (AQP4). Studies revealed that acute inhibition of AQP4 after stroke diminishes brain edema, however, its effect on peri-infarct astrocyte reactivity and the subacute outcome is unclear. And if diffusion-weighted imaging (DWI) could reflect the AQP4 expression patterns is uncertain.MethodsRats were subjected to middle cerebral artery occlusion (MCAO) and allocated randomly to TGN 020-treated and control groups. One day after stroke, brain swelling and lesion volumes of the rats were checked using T2-weighted imaging (T2-WI). Fourteen days after stroke, the rats successively underwent neurological examination, T2-WI and DWI with standard b-values and ultra-high b-values, apparent diffusion coefficient (ADC) was calculated correspondingly. Finally, the rats’ brains were acquired and used for glial fibrillary acidic protein (GFAP) and AQP4 immunoreactive analysis.ResultsAt 1 day after stroke, the TGN-020-treated animals exhibited reduced brain swelling and lesion volumes compared with those in the control group. At 14 days after stroke, the TGN-020-treated animals showed fewer neurological function deficits and smaller lesion volumes. In the peri-infarct region, the control group showed evident astrogliosis and AQP4 depolarization, which were reduced significantly in the TGN-020 group. In addition, the ultra-high b-values of ADC (ADCuh) in the peri-infarct region of the TGN-020 group was higher than that of the control group. Furthermore, correlation analysis revealed that peri-infarct AQP4 polarization correlated negatively with astrogliosis extent, and ADCuh correlated positively with AQP4 polarization.ConclusionWe found that acutely inhibiting AQP4 using TGN-020 promoted neurological recovery by diminishing brain edema at the early stage and attenuating peri-infarct astrogliosis and AQP4 depolarization at the subacute stage after stroke. Moreover, ADCuh could reflect the AQP4 polarization.

BackgroundMultimodal CT, including CT angiography (CTA) and CT perfusion (CTP), was increasingly used in stroke triage. This study was to determine the relationship between a new integrated parameter—both collateral circulation and relative permeability surface (PS)—and the hemorrhagic transformation (HT) in acute ischemic stroke (AIS) with middle cerebral artery occlusion (MCAO).MethodsWe retrospectively reviewed consecutive AIS patients with MCAO who underwent baseline CTA/CTP within 4 h of symptom onset and follow-up susceptibility-weighted imaging (SWI) within 3 weeks. Collateral circulation was assessed on the baseline CTA. Baseline CTP data were postprocessed to generate PS parameter. The patients with poor collateral circulation and at the same time with high relative PS were classified as the group of both poor collateral circulation and high relative PS. HT was defined according to European Cooperative Acute Stroke Study II criteria on follow-up SWI imaging. Multivariate logistic regression analysis was performed using HT as an outcome variable.ResultsThe group of patients with both poor collateral circulation and high relative PS was thirteen and thirty-three (52%) developed HT of the final cohort sixty-three AIS patients with MCAO. Multivariate logistic analysis revealed the new integrated parameter—both collateral circulation and relative PS (odds ratio, 16.59; 95% confidence interval, 13.09–19.10; P < 0.001) was independent predictor of HT. The area under the curve was 0.85 (95% confidence interval, 0.81–0.89). The sensitivity was 57%, specificity 97% and positive predictive value 92%, negative predictive value 58%.ConclusionsFor AIS patients with MCAO, these with poor collateral circulation on CTA and at the same time with high relative PS on CTP were at high risk for HT.

Background: Together with cerebral small vessel disease (CSVD), large vessel atherosclerosis is considered to be an equally important risk factor in the progression of vascular cognitive impairment. This article aims to investigate whether carotid atherosclerotic calcification is associated with the increased risk of post-stroke cognitive impairment (PSCI).Methods: A total of 128 patients (mean age: 62.1 ± 12.2 years, 37 women) suffering from ischemic stroke underwent brain/neck computer tomography angiography examination. The presence and characteristic of carotid calcification (size, number and location) were analyzed on computer tomography angiography. White matter hyperintensity (WMH) was assessed using Fazekas scales. PSCI was diagnosed based on a battery of neuropsychological assessments implemented 6−12 months after stroke.Results: Among 128 patients, 26 developed post-stroke dementia and 96 had carotid calcification. Logistic regression found carotid calcification (odds ratio [OR] = 7.15, 95% confidence interval [CI]: 1.07–47.69) and carotid artery stenosis (OR = 6.42, 95% CI: 1.03–40.15) both significantly increased the risk for post-stroke dementia. Moreover, multiple, thick/mixed, and surface calcifications exhibited an increasing trend in PSCI (Ptrend = 0.004, 0.016, 0.045, respectively). The prediction model for post-stroke dementia including carotid calcification (area under curve = 0.67), WMH (area under curve = 0.67) and other covariates yielded an area under curve (AUC) of 0.90 (95% CI: 0.82–0.99).Conclusion: Our findings demonstrated that the quantity and location of carotid calcifications were independent indicators for PSCI. The significant role of large vessel atherosclerosis in PSCI should be concerned in future study.

Chipless radio frequency identification (RFID) technology has been widely used in the field of structural health monitoring (SHM), but most of the current research mainly focuses on the detection of mechanical properties and there are few studies on the multi-physical parameters (for example, temperature and humidity) in the climatic environment around the structure. Thus, it is necessary to design a small and compact sensor for multi-parameter detection. This paper proposes a multi-parameter chipless RFID sensor based on microstrip coupling, which supports 4-bit ID code and integrates two detection functions of temperature and humidity. Through linear normalization fitting, the sensitivity of the sensor is about 2.18 MHz/RH in the ambient relative humidity test and the sensitivity of the sensor is about 898.63 KHz/°C in the experimental test of water bath heating from 24.6 °C to 75 °C. In addition, this paper proposes an engineering application detection method, designs a lightweight dynamic spectrum detection and wireless transmission platform based on a lightweight vector network analyzer (VNA) and realizes the real-time extraction and transmission of RFID spectrum sensing data. The means are more flexible and economical than traditional experimental scenarios.