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The enumeration of EpCAM-positive circulating tumor cells (CTCs) has allowed estimation of overall metastatic burden in breast cancer patients. However, a thorough understanding of CTCs associated with breast cancer brain metastasis (BCBM) is necessary for early identification and evaluation of treatment response to BCBM. Here we report that BCBM CTCs is enriched in a distinct sub-population of cells identifiable by their biomarker expression and mutational content. Deriving from a comprehensive analysis of CTC transcriptomes, we discovered a unique “circulating tumor cell gene signature” that is distinct from primary breast cancer tissues. Further dissection of the circulating tumor cell gene signature identified signaling pathways associated with BCBM CTCs that may have roles in potentiating BCBM. This study proposes CTC biomarkers and signaling pathways implicated in BCBM that may be used either as a screening tool for brain micro-metastasis detection or for making rational treatment decisions and monitoring therapeutic response in patients with BCBM. Characterization of CTCs derived from breast cancer patients with brain metastasis (BCBM) may allow for early diagnosis of brain metastasis and/or help for treatment choice and its efficacy. In this study, the authors identify a unique signature, based on patient-derived CTCs transcriptomes, for BCBM- CTCs that is different from primary tumors.

Intratumoral infiltration of myeloid-derived suppressor cells (MDSCs) is known to promote neoplastic growth by inhibiting the tumoricidal activity of T cells. However, direct interactions between patient-derived MDSCs and circulating tumors cells (CTCs) within the microenvironment of blood remain unexplored. Dissecting interplays between CTCs and circulatory MDSCs by heterotypic CTC/MDSC clustering is critical as a key mechanism to promote CTC survival and sustain the metastatic process. We characterized CTCs and polymorphonuclear-MDSCs (PMN-MDSCs) isolated in parallel from peripheral blood of metastatic melanoma and breast cancer patients by multi-parametric flow cytometry. Transplantation of both cell populations in the systemic circulation of mice revealed significantly enhanced dissemination and metastasis in mice co-injected with CTCs and PMN-MDSCs compared to mice injected with CTCs or MDSCs alone. Notably, CTC/PMN-MDSC clusters were detected in vitro and in vivo either in patients’ blood or by longitudinal monitoring of blood from animals. This was coupled with in vitro co-culturing of cell populations, demonstrating that CTCs formed physical clusters with PMN-MDSCs; and induced their pro-tumorigenic differentiation through paracrine Nodal signaling, augmenting the production of reactive oxygen species (ROS) by PMN-MDSCs. These findings were validated by detecting significantly higher Nodal and ROS levels in blood of cancer patients in the presence of naïve, heterotypic CTC/PMN-MDSC clusters. Augmented PMN-MDSC ROS upregulated Notch1 receptor expression in CTCs through the ROS-NRF2-ARE axis, thus priming CTCs to respond to ligand-mediated (Jagged1) Notch activation. Jagged1-expressing PMN-MDSCs contributed to enhanced Notch activation in CTCs by engagement of Notch1 receptor. The reciprocity of CTC/PMN-MDSC bi-directional paracrine interactions and signaling was functionally validated in inhibitor-based analyses, demonstrating that combined Nodal and ROS inhibition abrogated CTC/PMN-MDSC interactions and led to a reduction of CTC survival and proliferation. This study provides seminal evidence showing that PMN-MDSCs, additive to their immuno-suppressive roles, directly interact with CTCs and promote their dissemination and metastatic potency. Targeting CTC/PMN-MDSC heterotypic clusters and associated crosstalks can therefore represent a novel therapeutic avenue for limiting hematogenous spread of metastatic disease.

As the core equipment of pumped storage power stations, the erosion and wear of pump-turbine runner blades have become critical issues affecting the operational efficiency and service life of units. To mitigate particle impact energy and surface wear of the runner blades, this study proposes the installation of aeration short pipes with a diameter of 4 mm and a length of 20 mm at the adjustable guide vanes and the main shaft, aiming to investigate the influence of air injection on erosion characteristics. Numerical simulations demonstrate that air injection significantly alters the flow characteristics in the runner region and establishes a coupling relationship between erosion distribution and different aeration concentrations and injection methods. Guide vane aeration effectively reduces sediment-induced erosion on the runner crown and blade working surface, while simultaneously leading to more localized erosion on the crown and band. In contrast, main shaft aeration increases erosion on the crown and blade working surface, and under high aeration concentrations, the erosion region exhibits a significant expansion trend.

As the prevalence of respiratory diseases continues to rise, inhalation therapy has emerged as a crucial method for their treatment. The effective transmission of medications within the respiratory tract is vital to achieve therapeutic outcomes. Given that most inhaled particles carry electrostatic charges, understanding the electrostatic effect on particle behavior in bifurcated tubes is of significant importance. This work combined Large Eddy Simulation-Lagrangian particle tracking (LES-LPT) technology to simulate particle behavior with three particle sizes (10, 20, and 50 μm) from G2 to G3 (“G” stands for generation) in bifurcated tubes, either with or without electrostatics, under typical human physiological conditions (Re = 1036). The results indicate that the electrostatic force has a significant effect on particle behavior in bifurcated tubes, which increases with particle size. Within the bifurcated tubes, the electrostatic force enhances particle movement in alignment with the secondary flow as well as intensifies the interaction of particles with local turbulent vortices and promotes particle dispersion rather than agglomeration. On the other hand, the distribution of the electrostatic field is influenced by particle behavior. Higher particle concentration presents stronger electrostatic strength, which increases with particle size. Therefore, it can be concluded that the electrostatic interactions among particles can prevent particles from aggregating and enhance the efficiency of inhalation therapy.

Targeting thioredoxin reductase (TXNRD) with low-weight molecules is emerging as a high-efficacy anti-cancer strategy in chemotherapy. Sanguinarine has been reported to inhibit the activity of TXNRD1, indicating that benzophenanthridine alkaloid is a fascinating chemical entity in the field of TXNRD1 inhibitors. In this study, the inhibition of three benzophenanthridine alkaloids, including chelerythrine, sanguinarine, and nitidine, on recombinant TXNRD1 was investigated, and their anti-cancer mechanisms were revealed using three gastric cancer cell lines. Chelerythrine and sanguinarine are more potent inhibitors of TXNRD1 than nitidine, and the inhibitory effects take place in a dose- and time-dependent manner. Site-directed mutagenesis of TXNRD1 and in vitro inhibition analysis proved that chelerythrine or sanguinarine is primarily bound to the Sec498 residue of the enzyme, but the neighboring Cys497 and remaining N-terminal redox-active cysteines could also be modified after the conjugation of Sec498. With high similarity to sanguinarine, chelerythrine exhibited cytotoxic effects on multiple gastric cancer cell lines and suppressed the proliferation of tumor spheroids derived from NCI-N87 cells. Chelerythrine elevated cellular levels of reactive oxygen species (ROS) and induced endoplasmic reticulum (ER) stress. Moreover, the ROS induced by chelerythrine could be completely suppressed by the addition of N-acetyl-L-cysteine (NAC), and the same is true for sanguinarine. Notably, Nec-1, an RIPK1 inhibitor, rescued the chelerythrine-induced rapid cell death, indicating that chelerythrine triggers necroptosis in gastric cancer cells. Taken together, this study demonstrates that chelerythrine is a novel inhibitor of TXNRD1 by targeting Sec498 and possessing high anti-tumor properties on multiple gastric cancer cell lines by eliciting necroptosis.

Pre-existing comorbidities are linked to increased risk of severe COVID-19, but comprehensive assessments of comorbidity patterns remain limited. We used network analysis to identify pre-existing comorbidity modules (i.e., groups of diseases more densely interconnected with each other than with other diseases in the comorbidity network) in a cohort of 420,920 individuals from the UK Biobank who were in England. We defined cases requiring hospitalization or who died of COVID-19 as \"severe COVID-19\". Logistic regression was used to examine associations between comorbidity modules and severe COVID-19, and a module-based comorbidity index was developed to predict severe COVID-19, compared with existing indices. Comorbidity network analysis identified 190 disease pairs with confirmed comorbidity associations, which were further divided into seven comorbidity modules. Among the 30,914 individuals diagnosed with COVID-19, 3,970 were identified as severe cases (median age of 73.6 years, 58.77% being male). Six of seven identified modules showed statistically significant associations with severe COVID-19, especially modules related to circulatory and respiratory diseases (odds ratio = 1.67 [95% confidence interval 1.54-1.81]) and age-related eye diseases (1.39 [1.27-1.52]). Associations did not differ by sex, age or vaccination status but were generally stronger during the first wave of COVID-19 pandemic (i.e., 31st January-1st October, 2020). Our newly developed module-based comorbidity index showed better performance in predicting severe COVID-19 (AUC = 0.779) compared to the existing Charlson Comorbidity Index (0.714) and the 16-comorbidity index (0.714). Our study demonstrated that pre-existing comorbidity modules, particularly modules related to circulatory and respiratory diseases and age-related eye diseases, were associated with severe COVID-19. Moreover, the module-based comorbidity index provides better prediction of severe COVID-19 than existing prediction indices.

Macrophages secrete a variety of pro-inflammatory cytokines in response to pathogen-associated molecular patterns (PAMPs) and damage-associated molecular patterns (DAMPs) but abnormal release of cytokines unfortunately promotes cytokine storms. Dimethyl fumarate (DMF), an FDA-approved drug for multiple sclerosis (MS) treatment, has been found as an effective therapeutic agent for resolution. In this study, the anti-inflammatory effect of DMF was found to correlate to selenoprotein thioredoxin reductase 1 (TXNRD1). DMF irreversibly modified the Sec498 residue and C-terminal catalytic cysteine residues of TXNRD1 in a time- and dose-dependent manner. In LPS-stimulated RAW 264.7 cells, cellular TXNRD activity was increased through up-regulation of the protein level and DMF inhibited TXNRD activity and the nitric oxide (NO) production of RAW 264.7 cells. Meanwhile, the inhibition of TXNRD1 by DMF would contribute to the redox regulation of inflammation and promote the nuclear factor erythroid 2-related factor 2 (NRF2) activation. Notably, inhibition of cellular TXNRD1 by auranofin or TRi-1 showed anti-inflammatory effect in RAW 264.7 cells. This finding demonstrated that targeting TXNRD1 is a potential mechanism of using immunometabolites for dousing inflammation in response to pathogens and highlights the potential of TXNRD1 inhibitors in immune regulation.

is a promising marine fishery species, but visceral white-nodules disease (VWND) caused by causes significant losses. However, genetic resistance mechanisms to VWND remain elusive in this species. This study combined genome-wide association study (GWAS) and transcriptome analysis to unravel resistance loci and transcriptional regulation in . As a result, GWAS on 946 infected fish genotyped by 100 K lipid chips identified 22 suggestive significantly associated single-nucleotide polymorphisms (SNPs), annotated 60 candidate genes, where DNA-sensing pathway were enriched. RNA-seq on liver tissues of resistant, sensitive, and control groups found immune-related pathways enriched in the comparisons of RL vs CL and RL vs SL, and autophagy-related pathways enriched in the comparisons of SL vs CL and RL vs SL. Then, the integration of GWAS and transcriptome analysis identified seven key genes associated with resistance to VWND. Among the genes, the expression levels of mRNA for genes related to the cyclic GMP-AMP synthase-stimulator of interferon genes (STING) signaling pathway, as well as the protein levels of STING1, were significantly upregulated in RL. Collectively, integrating KEGG pathway analysis, gene and protein expression analysis revealed that the importance of STING1 for VWND resistance. These findings deepen the available knowledge on molecular mechanisms of host genetic resistance to VWND and provide an important foundation for the selection and breeding of VWND-resistant .

Background Large-scale medical equipment, which is extensively implemented in medical services, is of vital importance for diagnosis but vulnerable to various anomalies and failures. Most hospitals that conduct regular maintenance have been suffering from medical equipment-related incidents for years. Currently, the Internet of Medical Things (IoMT) has emerged as a crucial tool in monitoring the real-time status of the medical equipment. In this paper, we develop an IoMT system of Computed Tomography (CT) equipment in the West China Hospital, Sichuan University and collected the system status time-series data. Novel multivariate time-series classification models and frameworks are proposed to predict the anomalies of CT equipment. The important features that are closely related to the equipment anomalies are identified with the model. Methods We extracted the real-time CT equipment status time-series data of 11 equipment between May 19, 2020 and May 19, 2021 from the IoMT, which includes the equipment oil temperature, anode voltage, etc. The arcs are identified as labels of anomalies due to their relationship with decreased imaging quality and CT equipment failures. To improve prediction accuracy, the statistics and transformations of the raw historical time-series data segment in the sliding time window are used to construct new features. Due to the particularity of time-series data, two frameworks are proposed for splitting the training and test sets. Then the Decision Tree, Support Vector Machine, Logistic Regression, Naive Bayesian, and K-Nearest Neighbor classification models are used to classify the system status. We also compare our model to state-of-the-art models. Results The results show that the anomaly prediction accuracy and recall of our method are 79% and 77%, respectively. The oil temperature and anode voltage are identified as the decisive features that may lead to anomalies. The proposed model outperforms the others when predicting the anomalies of the CT equipment based on our dataset. Conclusions The proposed method could predict the state of CT equipment and be used as a reference for practical maintenance, where unexpected anomalies of medical equipment could be reduced. It also brings new insights into how to handle non-uniform and imbalanced time series data in practical cases.

Background Adverse childhood experiences (ACEs), including childhood maltreatment, have been linked with increased risk of diabetes and obesity during adulthood. A comprehensive assessment on the associations between childhood maltreatment and all major endocrine diseases, as well as the relative importance of different proposed mechanistic pathways on these associations, is currently lacking. Methods Based on the UK Biobank, we constructed a cohort including 151,659 participants with self-reported data on childhood maltreatment who were 30 years of age or older on/after January 1, 1985. All participants were followed from the index date (i.e., January 1, 1985, or their 30th birthday, whichever came later) until the first diagnosis of any or specific (12 individual diagnoses and 9 subtypes) endocrine diseases, death, or the end of follow-up (December 31, 2019), whichever occurred first. We used Cox models to examine the association of childhood maltreatment, treated as continuous (i.e., the cumulative number of experienced childhood maltreatment), ordinal (i.e., 0, 1 and ≥ 2), or binary (< 2 and ≥ 2) variable, with any and specific endocrine diseases, adjusted for multiple covariates. We further examined the risk of having multiple endocrine diseases using Linear or Logistic Regression models. Then, sequential mediation analyses were performed to assess the contribution of four possible mechanisms (i.e., suboptimal socioeconomic status (SES), psychological adversities, unfavorable lifestyle, and biological alterations) on the observed associations. Results During an average follow-up of 30.8 years, 20,885 participants received a diagnosis of endocrine diseases. We observed an association between the cumulative number of experienced childhood maltreatment and increased risk of being diagnosed with any endocrine disease (adjusted hazard ratio (HR) = 1.10, 95% confidence interval 1.09–1.12). The HR was 1.26 (1.22–1.30) when comparing individuals ≥ 2 with those with < 2 experienced childhood maltreatment. We further noted the most pronounced associations for type 2 diabetes (1.40 (1.33–1.48)) and hypothalamic–pituitary–adrenal (HPA)-axis-related endocrine diseases (1.38 (1.17–1.62)), and the association was stronger for having multiple endocrine diseases, compared to having one (odds ratio (95% CI) = 1.24 (1.19–1.30), 1.35 (1.27–1.44), and 1.52 (1.52–1.53) for 1, 2, and ≥ 3, respectively). Sequential mediation analyses showed that the association between childhood maltreatment and endocrine diseases was consistently and most distinctly mediated by psychological adversities (15.38 ~ 44.97%), while unfavorable lifestyle (10.86 ~ 25.32%) was additionally noted for type 2 diabetes whereas suboptimal SES (14.42 ~ 39.33%) for HPA-axis-related endocrine diseases. Conclusions Our study demonstrates that adverse psychological sequel of childhood maltreatment constitutes the main pathway to multiple endocrine diseases, particularly type 2 diabetes and HPA-axis-related endocrine diseases. Therefore, increased access to evidence-based mental health services may also be pivotal in reducing the risk of endocrine diseases among childhood maltreatment-exposed individuals.