Promoting In Vivo NIR-II Fluorescent Imaging for Lipid in Lipid Metabolism Diseases Diagnosis.

Lipid metabolism diseases have become a tremendous risk worldwide, along with the development of productivity and particular attention to public health. It has been an urgent necessity to exploit reliable imaging strategies for lipids and thus to monitor fatty liver diseases. Herein, by converting the NIR-I signal to the NIR-II signal with IR1061 for the monitoring of lipid, the in vivo imaging of fatty liver disease was promoted on the contrast and visual effect. The main advantages of the imaging promotion in this work included a long emission wavelength, rapid response, and high signal-background-ratio (SBR) value. After promoting the NIR-I signal to NIR-II signal, IR1061 achieved higher SBR value and exhibited a dose-dependent fluorescence intensity at 1100 nm along with the increase of the EtOH proportion as well as steady and selective optical responses toward liposomes. IR1061 was further applied in the in vivo imaging of lipid in fatty liver diseases. In spite of the differences in body weight gain and TC level between healthy mice and fatty liver diseases two models, IR1061 achieved high-resolution imaging in the liver region to monitor the fatty liver disease status. This work might be informatic for the clinical diagnosis and therapeutical treatments of fatty liver diseases.

Artificial intelligence-assisted system for the assessment of Forrest classification of peptic ulcer bleeding: a multicenter diagnostic study.

BACKGROUND: Inaccurate Forrest classification may significantly affect clinical outcomes, especially in high risk patients. Therefore, this study aimed to develop a real-time deep convolutional neural network (DCNN) system to assess the Forrest classification of peptic ulcer bleeding (PUB). METHODS: A training dataset (3868 endoscopic images) and an internal validation dataset (834 images) were retrospectively collected from the 900th Hospital, Fuzhou, China. In addition, 521 images collected from four other hospitals were used for external validation. Finally, 46 endoscopic videos were prospectively collected to assess the real-time diagnostic performance of the DCNN system, whose diagnostic performance was also prospectively compared with that of three senior and three junior endoscopists. RESULTS: The DCNN system had a satisfactory diagnostic performance in the assessment of Forrest classification, with an accuracy of 91.2% (95%CI 89.5%-92.6%) and a macro-average area under the receiver operating characteristic curve of 0.80 in the validation dataset. Moreover, the DCNN system could judge suspicious regions automatically using Forrest classification in real-time videos, with an accuracy of 92.0% (95%CI 80.8%-97.8%). The DCNN system showed more accurate and stable diagnostic performance than endoscopists in the prospective clinical comparison test. This system helped to slightly improve the diagnostic performance of senior endoscopists and considerably enhance that of junior endoscopists. CONCLUSION: The DCNN system for the assessment of the Forrest classification of PUB showed satisfactory diagnostic performance, which was slightly superior to that of senior endoscopists. It could therefore effectively assist junior endoscopists in making such diagnoses during gastroscopy.

PRDX1 exerts a photoprotection effect by inhibiting oxidative stress and regulating MAPK signaling on retinal pigment epithelium.

BACKGROUND: The purpose of this study was to investigate the photoprotection effect of peroxiredoxin 1 (PRDX1) protein in ultraviolet B (UVB) irradiation-induced damage of retinal pigment epithelium (RPE) and its possible molecular mechanism. METHODS: ARPE-19 cell viability and apoptosis were assessed by MTT assay and flow cytometry, respectively. Real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to detect the PRDX1 expression. The corresponding kits were employed to measure the levels or activities of lactate dehydrogenase (LDH), 8-hydroxy-2-deoxyguanosine (8-OHdG), reactive oxygen species (ROS), malondialdehyde (MDA), glutathione peroxidase (GSH-Px), superoxide dismutase (SOD). Western blotting was applied to examine PRDX1 expression and mitogen-activated protein kinase (MAPK) signaling pathway-related proteins. RESULTS: After exposure to 20 mJ/cm2 intensity of UVB irradiation for 24 h, ARPE-19 cells viability was decreased, the leakage degree of LDH and 8-OHdG were increased, and cell apoptosis was elevated. The expression of PRDX1 was significantly down-regulated in UVB-induced ARPE-19 cells. The low expression of PRDX1 was involved in high irradiation intensity. Overexpression of PRDX1 increased cell activity, decreased cell apoptosis, and LDH as well as 8-OHdG leakage in UVB-induced ARPE-19 cells. In addition to alleviating UVB-induced cell damage, PRDX1 overexpression also inhibited UVB-induced oxidative stress (down-regulation of ROS and MDA levels, up-regulation of GSH-Px and SOD activities) and the activation of MAPK signaling pathway in ARPE-19 cells. CONCLUSION: PRDX1 exerts a photoprotection effect on RPE by attenuating UVB-induced cell damage and inhibiting oxidative stress, which can be attributed to the inhibition of MAPK signaling pathway activation.

Individualized driver amplitude in liver MR elastography: a linear regression study.

BACKGROUND: Current liver magnetic resonance elastography (MRE) scans often require adjustments to driver amplitude to produce acceptable images. This could lead to time wastage and the potential loss of an opportunity to capture a high-quality image. PURPOSE: To construct a linear regression model of individualized driver amplitude to improve liver MRE image quality. MATERIAL AND METHODS: Data from 95 liver MRE scans of 61 participants, including abdominal missing volume ratio (AMVR), breath-holding status, the distance from the passive driver on the skin surface to the liver edge (Dd-l), body mass index (BMI), and lateral deflection of the passive driver with respect to the human sagittal plane (Angle α), were continuously collected. The Spearman correlation analysis and lasso regression were conducted to screen the independent variables. Multiple linear regression equations were developed to determine the optimal amplitude prediction model. RESULTS: The optimal formula for linear regression models: driver amplitude (%) = -16.80 + 78.59 × AMVR - 11.12 × breath-holding (end of expiration = 1, end of inspiration = 0) + 3.16 × Dd-l + 1.94 × BMI + 0.34 × angle α, with the model passing the F test (F = 22.455, P <0.001) and R2 value of 0.558. CONCLUSION: The individualized amplitude prediction model based on AMVR, breath-holding status, Dd-l, BMI, and angle α is a valuable tool in liver MRE examination.

Machine Learning Model for Predicting Axillary Lymph Node Metastasis in Clinically Node Positive Breast Cancer Based on Peritumoral Ultrasound Radiomics and SHAP Feature Analysis.

OBJECTIVE: This study seeks to construct a machine learning model that merges clinical characteristics with ultrasound radiomic analysis-encompassing both the intratumoral and peritumoral-to predict the status of axillary lymph nodes in patients with early-stage breast cancer. METHODS: The study employed retrospective methods, collecting clinical information, ultrasound data, and postoperative pathological results from 321 breast cancer patients (including 224 in the training group and 97 in the validation group). Through correlation analysis, univariate analysis, and Lasso regression analysis, independent risk factors related to axillary lymph node metastasis in breast cancer were identified from conventional ultrasound and immunohistochemical indicators, and a clinical feature model was constructed. Additionally, features were extracted from ultrasound images of the intratumoral and its 1-5 mm peritumoral to establish a radiomics feature formula. Furthermore, by combining clinical features and ultrasound radiomics features, six machine learning models (Logistic Regression, Decision Tree, Support Vector Machine, Extreme Gradient Boosting, Random Forest, and K-Nearest Neighbors) were compared for diagnostic efficacy, and constructing a joint prediction model based on the optimal ML algorithm. The use of Shapley Additive Explanations (SHAP) enhanced the visualization and interpretability of the model during the diagnostic process. RESULTS: Among the 321 breast cancer patients, 121 had axillary lymph node metastasis, and 200 did not. The clinical feature model had an AUC of 0.779 and 0.777 in the training and validation groups, respectively. Radiomics model analysis showed that the model including the Intratumor +3 mm peritumor area had the best diagnostic performance, with AUCs of 0.847 and 0.844 in the training and validation groups, respectively. The joint prediction model based on the XGBoost algorithm reached AUCs of 0.917 and 0.905 in the training and validation groups, respectively. SHAP analysis indicated that the Rad Score had the highest weight in the prediction model, playing a significant role in predicting axillary lymph node metastasis in breast cancer. CONCLUSION: The predictive model, which integrates clinical features and radiomic characteristics using the XGBoost algorithm, demonstrates significant diagnostic value for axillary lymph node metastasis in breast cancer. This model can provide significant references for preoperative surgical strategy selection and prognosis evaluation for breast cancer patients, helping to reduce postoperative complications and improve long-term survival rates. Additionally, the utilization of SHAP enhancing the global and local interpretability of the model.

Combining pathological risk factors and T, N staging to optimize the assessment for risk stratification and prognostication in low-risk stage III colon cancer.

BACKGROUND: This study aimed to investigate the combined pathological risk factors (PRFs) to stratify low-risk (pT1-3N1) stage III colon cancer (CC), providing a basis for individualized treatment in the future. PATIENTS AND METHODS: PRFs for low-risk stage III CC were identified using COX model. Low-risk stage III CC was risk-grouped combining with PRFs, and survival analysis were performed using Kaplan-Meier. The Surveillance, Epidemiology, and End Results (SEER) databases was used for external validation. RESULTS: Nine hundred sixty-two stage III CC patients were included with 634 (65.9%) as low risk and 328 (34.1%) as high risk. Poor differentiation (OS: P = 0.048; DFS: P = 0.011), perineural invasion (OS: P = 0.003; DFS: P < 0.001) and tumor deposits (OS: P = 0.012; DFS: P = 0.003) were identified as PRFs. The prognosis of low-risk CC combined with 2 PRFs (OS: HR = 3.871, 95%CI, 2.004-7.479, P < 0.001; DFS: HR = 3.479, 95%CI, 2.158-5.610, P < 0.001) or 3 PRFs (OS: HR = 5.915, 95%CI, 1.953-17.420, P = 0.002; DFS: HR = 5.915, 95%CI, 2.623-13.335, P < 0.001) was similar to that of high-risk CC (OS: HR = 3.927, 95%CI, 2.317-6.656, P < 0.001; DFS: HR = 4.132, 95%CI, 2.858-5.974, P < 0.001). In the SEER database, 18,547 CC patients were enrolled with 10,023 (54.0%) as low risk and 8524 (46.0%) as high risk. Low-risk CC combined with 2 PRFs (OS: HR = 1.857, 95%CI, 1.613-2.139, P < 0.001) was similar to that of high-risk CC without PRFs (HR = 1.876, 95%CI, 1.731-2.033, P < 0.001). CONCLUSION: Combined PRFs improved the risk stratification of low-risk stage III CC, which could reduce the incidence of undertreatment and guide adjuvant chemotherapy.

Rogue wave excitations and hybrid wave structures of the Heisenberg ferromagnet equation with time-dependent inhomogeneous bilinear interaction and spin-transfer torque.

In this paper, we focus on the localized rational waves of the variable-coefficient Heisenberg spin chain equation, which models the local magnetization in ferromagnet with time-dependent inhomogeneous bilinear interaction and spin-transfer torque. First, we establish the iterative generalized (m,N-m)-fold Darboux transformation of the Heisenberg spin chain equation. Then, the novel localized rational solutions (LRSs), rogue waves (RWs), periodic waves, and hybrid wave structures on the periodic, zero, and nonzero constant backgrounds with the time-dependent coefficients α(t) and ß(t) are obtained explicitly. Additionally, we provide the trajectory curves of magnetization and the variation of the magnetization direction for the obtained nonlinear waves at different times. These phenomena imply that the LRSs and RWs play the crucial roles in changing the circular motion of the magnetization. Finally, we also numerically simulate the wave propagations of some localized semi-rational solutions and RWs.

Therapeutic effects and molecular mechanisms of natural products in thrombosis.

Thrombotic disorders, such as myocardial infarction and stroke, are the leading cause of death in the global population and have become a health problem worldwide. Drug therapy is one of the main antithrombotic strategies, but antithrombotic drugs are not completely safe, especially the risk of bleeding at therapeutic doses. Recently, natural products have received widespread interest due to their significant efficacy and high safety, and an increasing number of studies have demonstrated their antithrombotic activity. In this review, articles from databases, such as Web of Science, PubMed, and China National Knowledge Infrastructure, were filtered and the relevant information was extracted according to predefined criteria. As a result, more than 100 natural products with significant antithrombotic activity were identified, including flavonoids, phenylpropanoids, quinones, terpenoids, steroids, and alkaloids. These compounds exert antithrombotic effects by inhibiting platelet activation, suppressing the coagulation cascade, and promoting fibrinolysis. In addition, several natural products also inhibit thrombosis by regulating miRNA expression, anti-inflammatory, and other pathways. This review systematically summarizes the natural products with antithrombotic activity, including their therapeutic effects, mechanisms, and clinical applications, aiming to provide a reference for the development of new antithrombotic drugs.

Study on diagnosing thyroid nodules of ACR TI-RADS 4-5 with multimodal ultrasound radiomics technology.

BACKGROUND: Explore the feasibility of using the multimodal ultrasound (US) radiomics technology to diagnose American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) 4-5 thyroid nodules. METHOD: This study prospectively collected the clinical characteristics, conventional, and US elastography images of 100 patients diagnosed with ACR TI-RADS 4-5 nodules from May 2022 to 2023. Independent risk factors for malignant thyroid nodules were extracted and screened using methods such as the least absolute shrinkage and selection operator (LASSO) logistic regression (LR) model, and a multimodal US radiomics combined diagnostic model was established. Using a multifactorial LR analysis and a Rad-score rating, the predictive performance was validated and evaluated, and the final threshold range was determined to assess the clinical net benefit of the model. RESULTS: In the training set, the US radiomics combined predictive model area under curve (AUC = 0.928) had higher diagnostic performance compared with clinical characteristics (AUC = 0.779), conventional US (AUC = 0.794), and US elastography model (AUC = 0.852). In the validation set, the multimodal US radiomics combined diagnostic model (AUC = 0.829) also had higher diagnostic performance compared with clinical characteristics (AUC = 0.799), conventional US (AUC = 0.802), and US elastography model (AUC = 0.718). CONCLUSION: Multi-modal US radiomics technology can effectively diagnose thyroid nodules of ACR TI-RADS 4-5, and the combination of radiomics signature and conventional US features can further improve the diagnostic performance.

Role and therapeutic potential of gelsolin in atherosclerosis.

Atherosclerosis is the major pathophysiological basis of a variety of cardiovascular diseases and has been recognized as a lipid-driven chronic inflammatory disease. Gelsolin (GSN) is a member of the GSN family. The main function of GSN is to cut and seal actin filaments to regulate the cytoskeleton and participate in a variety of biological functions, such as cell movement, morphological changes, metabolism, apoptosis and phagocytosis. Recently, more and more evidences have demonstrated that GSN is Closely related to atherosclerosis, involving lipid metabolism, inflammation, cell proliferation, migration and thrombosis. This article reviews the role of GSN in atherosclerosis from inflammation, apoptosis, angiogenesis and thrombosis.

Clustering-Evolved Frontier Orbital for Low-Temperature CO2 Dissociation.

In this study, single Ni2 clusters (two Ni atoms bridged by a lattice oxygen) are successfully synthesized on monolayered CuO. They exhibit a remarkable activity toward low-temperature CO2 thermal dissociation, in contrast to cationic Ni atoms that nondissociatively adsorb CO2 and metallic Ni ones that are chemically inert for CO2 adsorption. Density functional theory calculations reveal that the Ni2 clusters can significantly alter the spatial symmetry of their unoccupied frontier orbitals to match the occupied counterpart of the CO2 molecule and enable its low-temperature dissociation. This study may help advance single-cluster catalysis and exploit the unexcavated mechanism for low-temperature CO2 activation.

High-Density Coordinatively Unsaturated Zn Catalyst for Efficient Alkane Dehydrogenation.

The exploration of non-noble metal catalysts for alkane dehydrogenation and their catalytic mechanisms is the priority in catalysis research. Here, we report a high-density coordinatively unsaturated Zn cation (Zncus) catalyst for the direct dehydrogenation (DDH) of ethylbenzene (EB) to styrene (ST). The catalyst demonstrated good catalytic performance (∼40% initial EB conversion rate and >98% ST selectivity) and excellent regeneration ability in the reaction, which is attributed to the high-density (HD) distribution and high-stability structure of Zncus active sites on the surface of zinc silicate (HD-Zncus@ZS). Density functional theory (DFT) calculations further illustrated the reaction pathway and intermediates, supporting that the Zncus sites can efficiently activate the C-H bond of ethyl on ethylbenzene. Developing the high-density Zncus catalyst and exploring the catalytic mechanism laid a good foundation for designing practical non-noble metal catalysts.

The Canadian Rare Diseases Models and Mechanisms (RDMM) Network: Connecting Understudied Genes to Model Organisms.

Advances in genomics have transformed our ability to identify the genetic causes of rare diseases (RDs), yet we have a limited understanding of the mechanistic roles of most genes in health and disease. When a novel RD gene is first discovered, there is minimal insight into its biological function, the pathogenic mechanisms of disease-causing variants, and how therapy might be approached. To address this gap, the Canadian Rare Diseases Models and Mechanisms (RDMM) Network was established to connect clinicians discovering new disease genes with Canadian scientists able to study equivalent genes and pathways in model organisms (MOs). The Network is built around a registry of more than 500 Canadian MO scientists, representing expertise for over 7,500 human genes. RDMM uses a committee process to identify and evaluate clinician-MO scientist collaborations and approve 25,000 Canadian dollars in catalyst funding. To date, we have made 85 clinician-MO scientist connections and funded 105 projects. These collaborations help confirm variant pathogenicity and unravel the molecular mechanisms of RD, and also test novel therapies and lead to long-term collaborations. To expand the impact and reach of this model, we made the RDMM Registry open-source, portable, and customizable, and we freely share our committee structures and processes. We are currently working with emerging networks in Europe, Australia, and Japan to link international RDMM networks and registries and enable matches across borders. We will continue to create meaningful collaborations, generate knowledge, and advance RD research locally and globally for the benefit of patients and families living with RD.

Imaging Investigation of Hepatocellular Carcinoma Progress via Monitoring γ-Glutamyltranspeptidase Level with a Near-Infrared Fluorescence/Photoacoustic Bimodal Probe.

Hepatocellular carcinoma (HCC) is one of the main principal causes of cancer death, and the late definite diagnosis limits therapeutic approaches in time. The early diagnosis of HCC is essential, and the previous investigations on the biomarkers inferred that the γ-glutamyltranspeptidase (GGT) level could indicate the HCC process. Herein, a near-infrared fluorescence/photoacoustic (NIRF/PA) bimodal probe, CySO3-GGT, was developed for monitoring the GGT level and thus to image the HCC process. After the in-solution tests, the bimodal response was convinced. The various HCC processes were imaged by CySO3-GGT at the cellular level. Then, the CCl4-induced HCC (both induction and treatment) and the subcutaneous and orthotopic xenograft mice models were selected. All throughout the tests, CySO3-GGT achieved NIRF and PA bimodal imaging of the HCC process. In particular, CySO3-GGT could effectively realize 3D imaging of the HCC nodule by visualizing the boundary between the tumor and the normal tissue. The information here might offer significant guidance for the dynamic monitoring of HCC in the near future.

Immunized Microspheres Engineered Hydrogel Membrane for Reprogramming Macrophage and Mucosal Repair.

The "double-edged sword" effect of macrophages under the influence of different microenvironments determines the outcome and prognosis of tissue injury. Accurate and stable reprogramming macrophages (Mφ) are the key to rapid wound healing. In this study, an immunized microsphere-engineered GelMA hydrogel membrane is constructed for oral mucosa treatment. The nanoporous poly(lactide-co-glycolide) (PLGA) microsphere drug delivery system combined with the photo-cross-linkable hydrogel is used to release the soybean lecithin (SL)and IL-4 complexes (SL/IL-4) sustainedly. In this way, it is realized effective wound fit, improvement of drug encapsulation, and stable triphasic release of interleukin-4 (IL-4). In both in vivo and in vitro experiments, it is demonstrated that the hydrogel membrane can reprogram macrophages in the microenvironment into M2Mφ anti-inflammatory types, thereby inhibiting the local excessive inflammatory response. Meanwhile, high levels of platelet-derived growth factor (PDGF) secreted by M2Mφ macrophages enhanced neovascular maturation by 5.7-fold, which assisted in achieving rapid healing of oral mucosa. These findings suggest that the immuno-engineered hydrogel membrane system can re-modulating the biological effects of Mφ, and potentiating the maturation of neovascularization, ultimately achieving the rapid repair of mucosal tissue. This new strategy is expected to be a safe and promising immunomodulatory biomimetic material for clinical translation.

Drug repurposing for COVID-19: could vitamin C combined with glycyrrhizic acid be at play by the findings of Li et al.'s database-based network pharmacology analysis?

The outbreak and pandemic of SARS-CoV-2 in 2019 has caused a severe public health burden and will challenge global health for the future. The discovery and mechanistic investigation of drugs against Coronavirus disease 2019 (COVID-19) is in deadly demand. The paper published by Li and colleagues proposed the hypothesis that vitamin C combined with glycyrrhizic acid in treating COVID-19 and its mechanistic investigation was performed by a database-based network pharmacology. In this letter, we present critical comments on the limitations and insufficiencies involved, from both the perspective of network pharmacology and current evidence on COVID-19.

Portraying the dark side of endogenous IFN-λ for promoting cancer progression and immunoevasion in pan-cancer.

BACKGROUND: IFN-λ has been shown to have a dual function in cancer, with its tumor-suppressive roles being well-established. However, the potential existence of a negative ''tumor-promoting'' effect of endogenous IFN-λ is still not fully understood. METHODS: We conducted a comprehensive review and analysis of the perturbation of IFN-λ genes across various cancer types. Correlation coefficients were utilized to examine the relationship between endogenous IFN-λ expression and clinical factors, immune cell infiltration, tumor microenvironment, and response to immunotherapy. Genes working together with IFN-λ were obtained by constructing the correlation-based network related to IFN-λ and the gene interaction network in the KEGG pathway and IFN-λ-related genes obtained from the networks were integrated as candidate markers for the prognosis model. We then applied univariate and multivariate COX regression models to select cancer-specific independent prognostic markers associated with IFN-λ and to investigate risk factors for these genes by survival analysis. Additionally, computational methods were used to analyze the transcriptome, copy number variations, genetic mutations, and methylation of IFN-λ-related patient groups. RESULT: Endogenous expression of IFN-λ has been linked to poor prognosis in cancer patients, with the genes IFN-λ2 and IFN-λ3 serving as independent prognostic markers. IFN-λ acts in conjunction with related genes such as STAT1, STAT2, and STAT3 to affect the JAK-STAT signaling pathway, which promotes tumor progression. Abnormalities in IFN-λ genes are associated with changes in immune checkpoints and immune cell infiltration, which in turn affects cancer- and immune-related pathways. While there is increased immune cell infiltration in patients with IFN-λ expression, this does not improve survival prognosis, as T-cell dysfunction and an inflammatory environment are also present. The amplification of IFNL2 and IFNL3 copy number variants drives specific endogenous expression of IFN-λ in patients, and those with this specific expression have been found to have more mutations in the TP53 gene and lower levels of DNA methylation. CONCLUSION: Our study integrated multi-omics data to provide a comprehensive insight into the dark side of endogenous IFN-λ, providing a fundamental resource for further discovery and therapeutic exploration in cancer.

Streptococcus strain D19T as a probiotic candidate to modulate oral health.

BACKGROUND: As probiotics protect host cells, they are used to treat bacterial infections. It has been indicated that probiotics may prevent or reduce the attachment of pathogens to host cells. In this study, Streptococcus strain D19T was isolated from the oropharynx of a healthy child, and its adhesion performance and Staphylococcus aureus adhesion inhibition effect were analysed using human bronchial epithelial (16-HBE) cells, as an in vitro cell model. We evaluated the probiotic properties of the D19T strain based on its acid-base, bile salt, and lysozyme tolerance; antibacterial activity; cytotoxicity; antibiotic sensitivity; in vitro adhesion to 16-HBE cells; and competitive, exclusion, and displacement effects against S. aureus. RESULTS: Streptococcus strain D19T showed tolerance to a PH range of 2-5 and 0.5-1% bile. However, it was more tolerant to 0.5% bile than to 1% bile. The strain also demonstrated an ability to adapt to maladaptive oropharyngeal conditions (i.e., tolerating 200 µg/mL lysozyme). It was resistant to 0.8 mM H2O2. The results also demonstrated that D19T exhibited inhibitory activities against various common pathogenic bacteria. Furthermore, D19T was not toxic to 16-HBE cells at different multiplicities of infection and was sensitive to most antibiotics tested. The adhesion rate of D19T cells to 16-HBE cells was 47% ± 1.2%, which was significantly higher than that of S. aureus to 16-HBE cells. The competition, exclusion, and displacement assay results showed that D19T has good inhibitory effect against S. aureus adhesion. CONCLUSIONS: The present study revealed that Streptococcus strain D19T has the potential to be developed as a respiratory microbiota preparations.

P T symmetry in a superconducting hybrid quantum system with longitudinal coupling.

We propose a scheme consisting of coupled nanomechanical cantilever resonators and superconducting flux qubits to engineer a parity-time- (P T-) symmetric phononic system formed by active and passive modes. The effective gain (loss) of the phonon mode is achieved by the longitudinal coupling of the resonator and the fast dissipative superconducting qubit with a blue-sideband driving (red-sideband driving). A P T-symmetric to broken-P T-symmetric phase transition can be observed in both balanced gain-to-loss and unbalanced gain-to-loss cases. Applying a resonant weak probe field to the dissipative resonator, we find that (i) for balanced gain and loss, the acoustic signal absorption to amplification can be tuned by changing the coupling strength between resonators; (ii) for unbalanced gain and loss, both acoustically induced transparency and anomalous dispersion can be observed around Δ = 0, where the maximum group delay is also located at this point. Our work provides an experimentally feasible scheme to design P T-symmetric phononic systems and a powerful platform for controllable acoustic signal transmission in a hybrid quantum system.

Notch3 restricts metastasis of breast cancers through regulation of the JAK/STAT5A signaling pathway.

PURPOSE: To explore the potential role of signal transducer and activator of transcription 5A (STAT5A) in the metastasis of breast cancer, and its mechanism of regulation underlying. METHODS AND RESULTS: TCGA datasets were used to evaluate the expression of STAT5A in normal and different cancerous tissues through TIMER2.0, indicating that STAT5A level was decreased in breast cancer tissues compared with normal ones. Gene Set Enrichment Analysis predicted that STAT5A was associated with the activation of immune cells and cell cycle process. We further demonstrated that the infiltration of immune cells was positively associated with STAT5A level. Influorescence staining revealed the expression and distribution of F-actin was regulated by STAT5A, while colony formation assay, wound healing and transwell assays predicted the inhibitory role of STAT5A in the colony formation, migratory and invasive abilities in breast cancer cells. In addition, overexpression of the Notch3 intracellular domain (N3ICD), the active form of Notch3, resulted in the increased expression of STAT5A. Conversely, silencing of Notch3 expression by siNotch3 decreased STAT5A expression, supporting that STAT5A expression is positively associated with Notch3 in human breast cancer cell lines and breast cancer tissues. Mechanistically, chromatin immunoprecipitation showed that Notch3 was directly bound to the STAT5A promoter and induced the expression of STAT5A. Moreover, overexpressing STAT5A partially reversed the enhanced mobility of breast cancer cells following Notch3 silencing. Low expression of Notch3 and STAT5A predicted poorer prognosis of patients with breast cancer. CONCLUSION: The present study demonstrates that Notch3 inhibits metastasis in breast cancer through inducing transcriptionally STAT5A, which was associated with tumor-infiltrating immune cells, providing a novel strategy to treat breast cancer.