Flexible Thermoelectric Device Based on Protrusion-Structured Liquid Metal Elastomer for Gravity Heat Pipe.

Monitoring the temperature of the coal gangue mountains is fundamental to preventing their spontaneous combustion. However, the existing temperature monitoring systems fail to achieve stable, pollution-free temperature monitoring without affecting vegetation growth in these mountains. To address this issue, this work proposes a flexible thermoelectric device (FTD) based on a protrusion-structured liquid metal elastomer (LME). Utilizing a high-thermal-conductivity LME, the FTD adheres closely to the surface of the gravity heat pipe (GHP), ensuring compatibility between FTD and the curved surface of the GHP. Simultaneously, employing a low-thermal-conductivity elastomer helps concentrate heat onto FTD, thereby enhancing thermoelectric power generation efficiency. Additionally, the impact of the shape, size, and height of the protrusion structure at the cold end of the GHP on its efficiency was also investigated. The practical application of FTD on GHP was demonstrated.

Prognosis prediction and risk stratification of breast cancer patients based on a mitochondria-related gene signature.

As the malignancy with the highest global incidence, breast cancer represents a significant threat to women's health. Recent advances have shed light on the importance of mitochondrial function in cancer, particularly in metabolic reprogramming within tumors. Recognizing this, we developed a novel risk signature based on mitochondrial-related genes to improve prognosis prediction and risk stratification in breast cancer patients. In this study, transcriptome data and clinical features of breast cancer samples were extracted from two sources: the TCGA, serving as the training set, and the METABRIC, used as the independent validation set. We developed the signature using LASSO-Cox regression and assessed its prognostic efficacy via ROC curves. Furthermore, the signature was integrated with clinical features to create a Nomogram model, whose accuracy was validated through clinical calibration curves and decision curve analysis. To further elucidate prognostic variations between high and low-risk groups, we conducted functional enrichment and immune infiltration analyses. Additionally, the study encompassed a comparison of mutation landscapes and drug sensitivity, providing a comprehensive understanding of the differing characteristics in these groups. Conclusively, we established a risk signature comprising 8 mitochondrial-related genes-ACSL1, ALDH2, MTHFD2, MRPL13, TP53AIP1, SLC1A1, ME3, and BCL2A1. This signature was identified as an independent risk predictor for breast cancer patient survival, exhibiting a significant high hazard ratio (HR = 3.028, 95%CI 2.038-4.499, P < 0.001). Patients in the low-risk group showed a more favorable prognosis, with enhanced immune infiltration, distinct mutation landscapes, and greater sensitivity to anti-tumor drugs. In contrast, the high-risk group exhibited an adverse trend in these aspects. This risk signature represents a novel and effective prognostic indicator, suggesting valuable insights for patient stratification in breast cancer.

Attention-Gated Deep-Learning-Based Automatic Digitization of Interstitial Needles in High-Dose-Rate Brachytherapy for Cervical Cancer.

Purpose: Deep learning can be used to automatically digitize interstitial needles in high-dose-rate (HDR) brachytherapy for patients with cervical cancer. The aim of this study was to design a novel attention-gated deep-learning model, which may further improve the accuracy of and better differentiate needles. Methods and Materials: Seventeen patients with cervical cancer with 56 computed tomography-based interstitial HDR brachytherapy plans from the local hospital were retrospectively chosen with the local institutional review board's approval. Among them, 50 plans were randomly selected as the training set and the rest as the validation set. Spatial and channel attention gates (AGs) were added to 3-dimensional convolutional neural networks (CNNs) to highlight needle features and suppress irrelevant regions; this was supposed to facilitate convergence and improve accuracy of automatic needle digitization. Subsequently, the automatically digitized needles were exported to the Oncentra treatment planning system (Elekta Solutions AB, Stockholm, Sweden) for dose evaluation. The geometric and dosimetric accuracy of automatic needle digitization was compared among 3 methods: (1) clinically approved plans with manual needle digitization (ground truth); (2) the conventional deep-learning (CNN) method; and (3) the attention-added deep-learning (CNN + AG) method, in terms of the Dice similarity coefficient (DSC), tip and shaft positioning errors, dose distribution in the high-risk clinical target volume (HR-CTV), organs at risk, and so on. Results: The attention-gated CNN model was superior to CNN without AGs, with a greater DSC (approximately 94% for CNN + AG vs 89% for CNN). The needle tip and shaft errors of the CNN + AG method (1.1 mm and 1.8 mm, respectively) were also much smaller than those of the CNN method (2.0 mm and 3.3 mm, respectively). Finally, the dose difference for the HR-CTV D90 using the CNN + AG method was much more accurate than that using CNN (0.4% and 1.7%, respectively). Conclusions: The attention-added deep-learning model was successfully implemented for automatic needle digitization in HDR brachytherapy, with clinically acceptable geometric and dosimetric accuracy. Compared with conventional deep-learning neural networks, attention-gated deep learning may have superior performance and great clinical potential.

Effect of edoxaban compared with other oral anticoagulants for stroke prevention in patients with atrial fibrillation: A meta-analysis.

Background and aim: Current observational studies have compared the effectiveness and safety of edoxaban with other oral anticoagulants in patients with AF, but the results are still disputed. This meta-analysis was conducted to compare the effect of edoxaban in patients with AF. Methods: We performed systematic research from the PubMed, EMBASE, and Cochrane Library databases until November 2022 to obtain relevant observational studies. Adjusted risk ratios (RRs) and 95 % confidence intervals (CIs) of the outcomes were collected and pooled by a random-effects model. This study was prospectively registered in PROSPERO (CRD42022314222). Results: A total of 17 observational studies were included in this meta-analysis. Compared with vitamin K antagonists, edoxaban was associated with lower risks of stroke or systemic embolism (RR = 0.67, 95 % CI:0.61-0.74), major bleeding (RR = 0.54, 95 % CI:0.44-0.67), and intracranial hemorrhage (RR = 0.51, 95 % CI:0.29-0.90). Compared with dabigatran or rivaroxaban, edoxaban was associated with reduced risks of stroke or systemic embolism (dabigatran [RR = 0.76, 95 % CI:0.66-0.87]; rivaroxaban [RR = 0.81, 95 % CI:0.70-0.94]) and major bleeding (dabigatran [RR = 0.82, 95 % CI:0.69-0.98]; rivaroxaban [RR = 0.81, 95 % CI:0.70-0.94]). Compared with apixaban, edoxaban was associated with a reduced risk of stroke or systemic embolism (RR = 0.87, 95 % CI:0.79-0.97), but had similar risks of bleeding events. Conclusions: Our current evidence suggested that edoxaban might have superior effectiveness and/or safety outcomes than vitamin K antagonists, dabigatran, rivaroxaban, and apixaban for stroke prevention in patients with AF.

Generalisation of radiotherapy dose calculation for Monte Carlo algorithm combined with 3D Swin-Unet: a multi-institutional IMRT evaluation.

Objective.Accurate dose calculations are essential prerequisites for precise radiotherapy. The integration of deep learning into dosimetry could consider computational accuracy and efficiency and has potential applicability to clinical dose calculation. The generalisation of a deep learning dose calculation method (hereinafter referred to as TERMA-Monte Carlo network, T-MC net) was evaluated in clinical practice using intensity-modulated radiotherapy (IMRT) plans for various human body regions and multiple institutions, with the Monte Carlo (MC) algorithm serving as a benchmark.Approach. Sixty IMRT plans were selected from four institutions for testing the head and neck, chest and abdomen, and pelvis regions. Using the MC results as the benchmark, the T-MC net calculation results were used to perform three-dimensional dose distribution and dose-volume histogram (DVH) comparisons of the entire body, planning target volume (PTV) and organs at risk (OARs), respectively, and calculate the mean ±95% confidence interval of gamma pass rate (GPR), percentage of agreement (PA) and dose difference ratio (DDR) of dose indices D95, D50, and D5.Main results. For the entire body, the GPRs of 3%/3 mm, 2%/2 mm, 2%/1 mm, and the PA were 99.62 ± 0.32%, 98.50 ± 1.09%, 95.60 ± 2.90% and 97.80 ± 1.12%, respectively. For the PTV, the GPRs of 3%/3 mm, 2%/2 mm, 2%/1 mm and the PA were 98.90 ± 1.00%, 95.78 ± 2.83%, 92.23 ± 4.74% and 98.93 ± 0.62%, respectively. The absolute value of average DDR was less than 1.4%.Significance. We proposed a general dose calculation framework based on deep learning, using the MC algorithm as a benchmark, performing a generalisation test for IMRT treatment plans across multiple institutions. The framework provides high computational speed while maintaining the accuracy of MC and may become an effective dose algorithm engine in treatment planning, adaptive radiotherapy, and dose verification.

ERCC6L facilitates the onset of mammary neoplasia and promotes the high malignance of breast cancer by accelerating the cell cycle.

BACKGROUND: Breast cancer (BC) is the leading cause of morbidity and the second leading cause of death among female malignant tumors. Although available drugs have been approved for the corresponding breast cancer subtypes (ER-positive, HER2+) currently, there are still no effective targeted drugs or treatment strategies for metastatic breast cancer or triple-negative breast cancer that lack targets. Therefore, it is urgent to discover new potential targets. ERCC6L is an essential protein involved in chromosome separation during cell mitosis. However, the effect of ERCC6L on the tumorigenesis and progression of breast cancer is unclear. METHODS AND RESULTS: Here, we found that ERCC6L was highly expressed in breast cancer, especially in TNBC, which was closely related to poor outcomes of patients. An ERCC6L conditional knockout mouse model was first established in this study, and the results confirmed that ERCC6L was required for the development of the mammary gland and the tumorigenesis and progression of mammary gland cancers. In in vitro cell culture, ERCC6L acted as a tumor promoter in the malignant progression of breast cancer cells. Overexpression of ERCC6L promoted cell proliferation, migration and invasion, while knockdown of ERCC6L caused the opposite results. Mechanistically, ERCC6L accelerated the cell cycle by regulating the G2/M checkpoint signalling pathway. Additionally, we demonstrated that there is an interaction between ERCC6L and KIF4A, both of which are closely related factors in mitosis and are involved in the malignant progression of breast cancer. CONCLUSIONS: We first demonstrated that ERCC6L deficiency can significantly inhibit the occurrence and development of mammary gland tumors. ERCC6L was found to accelerate the cell cycle by regulating the p53/p21/CDK1/Cyclin B and PLK/CDC25C/CDK1/Cyclin B signalling pathways, thereby promoting the malignant progression of breast cancer cell lines. There was a direct interaction between KIF4A and ERCC6L, and both are closely associated with mitosis and contribute to growth and metastasis of breast tumor. To sum up, our results suggest that ERCC6L may be used as a promising target for the treatment of BC.

Preliminary study on dosimetry characteristics of a novel cylindrical dose verification system.

OBJECTIVE: To develop a novel ionization chamber array dosimetry system, study its dosimetry characteristics, and perform preliminary tests for plan dose verification. METHODS: The dosimetry characteristics of this new array were tested, including short-term and long-term reproducibility, dose linearity, dose rate dependence, field size dependence, and angular dependence. The open field and MLC field plans were designed for dose testing. Randomly select 30 patient treatment plans (10 intensity-modulated radiation therapy [IMRT] plans and 20 volumetric modulated arc therapy [VMAT] plans) that have undergone dose verification using Portal Dosimetry to perform verification measurement and evaluate dose verification test results. RESULTS: The dosimetry characteristics of the arrays all performed well. The gamma passing rates (3%/2 mm) were more than 96% for the combined open field and MLC field plans. The average gamma pass rates were (99.54 ± 0.58)% and (96.70 ± 3.41)% for the 10 IMRT plans and (99.32 ± 0.89)% and (94.91 ± 6.01)% for the 20 VMAT plans at the 3%/2 mm and 2%/2 mm criteria, respectively, which is similar to the Portal Dosimetry's measurement results. CONCLUSIONS: This novel ionization chamber array demonstrates good dosimetry characteristics and is suitable for clinical IMRT and VMAT plan verifications.

MiR-3653 blocks autophagy to inhibit epithelial-mesenchymal transition in breast cancer cells by targeting the autophagy-regulatory genes ATG12 and AMBRA1.

BACKGROUND: Metastasis is the main cause of tumor-associated death and mainly responsible for treatment failure of breast cancer. Autophagy accelerates tumor metastasis. In our work, we aimed to investigate the possibility of microRNAs (miRNAs) which participate in the regulation of autophagy to inhibit tumor metastasis. METHODS: MiRNA array and comprehensive analysis were performed to identify miRNAs which participated in the regulation of autophagy to inhibit tumor metastasis. The expression levels of miR-3653 in breast cancer tissues and cells were detected by quantitative real-time polymerase chain reaction. In vivo and in vitro assays were conducted to determine the function of miR-3653. The target genes of miR-3653 were detected by a dual luciferase reporter activity assay and Western blot. The relationship between miR-3653 and epithelial-mesenchymal transition (EMT) was assessed by Western blot. Student's t -test was used to analyze the difference between any two groups, and the difference among multiple groups was analyzed with one-way analysis of variance and a Bonferroni post hoc test. RESULTS: miR-3653 was downregulated in breast cancer cells with high metastatic ability, and high expression of miR-3653 blocked autophagic flux in breast cancer cells. Clinically, low expression of miR-3653 in breast cancer tissues (0.054 ±â€Š0.013 vs . 0.131 ±â€Š0.028, t  = 2.475, P  = 0.014) was positively correlated with lymph node metastasis (0.015 ±â€Š0.004 vs . 0.078 ±â€Š0.020, t  = 2.319, P  = 0.023) and poor prognosis ( P  < 0.001). miR-3653 ameliorated the malignant phenotypes of breast cancer cells, including proliferation, migration (MDA-MB-231: 0.353 ±â€Š0.013 vs . 1.000 ±â€Š0.038, t  = 16.290, P  < 0.001; MDA-MB-468: 0.200 ±â€Š0.014 vs . 1.000 ±â€Š0.043, t  = 17.530, P  < 0.001), invasion (MDA-MB-231: 0.723 ±â€Š0.056 vs . 1.000 ±â€Š0.035, t  = 4.223, P  = 0.013; MDA-MB-468: 0.222 ±â€Š0.016 vs . 1.000 ±â€Š0.019, t  = 31.050, P  < 0.001), and colony formation (MDA-MB-231: 0.472 ±â€Š0.022 vs . 1.000 ±â€Š0.022, t  = 16.620, P  < 0.001; MDA-MB-468: 0.650 ±â€Š0.040 vs . 1.000 ±â€Š0.098, t  = 3.297, P  = 0.030). The autophagy-associated genes autophagy-related gene 12 ( ATG12 ) and activating molecule in beclin 1-regulated autophagy protein 1 ( AMBRA1 ) are target genes of miR-3653. Further studies showed that miR-3653 inhibited EMT by targeting ATG12 and AMBRA1 . CONCLUSIONS: Our findings suggested that miR-3653 inhibits the autophagy process by targeting ATG12 and AMBRA1 , thereby inhibiting EMT, and provided a new idea and target for the metastasis of breast cancer.

Recognition Imaging of Trace E-cadherins on the Bladder Cancer Cells Surface during Epithelial-Mesenchymal Transition by Force-Distance Curve-Based AFM.

Tumor-associated epithelial-mesenchymal transition (EMT) contains a set of transitional cellular states usually judged by the EMT marker expression. E-cadherin is a down-regulated EMT epithelial marker, and the detection of E-cadherin is challenging on cancer cell surfaces in the middle and late stages of EMT. Here, the trace E-cadherins on the living bladder cancer T24 cell surface during EMT were investigated with force-distance curve-based atomic force microscopy. The results confirmed that T24 cells are still in an intermediate state and can be transferred into the mesenchymal phenotype by long-term TGF-ß1 induction. During EMT, E-cadherins on the T24 cell surface gradually decreased and rarely clustered. E-cadherin is not completely missing, even at the end of EMT, but is too sparse to cluster. This work provides us with a visual understanding of the expression and distribution of trace markers during EMT and a deep comprehension of the indispensable significance of E-cadherin in cancer cells.

A novel non-invasive exhaled breath biopsy for the diagnosis and screening of breast cancer.

BACKGROUND: Early detection is critical for improving the survival of breast cancer (BC) patients. Exhaled breath testing as a non-invasive technique might help to improve BC detection. However, the breath test accuracy for BC diagnosis is unclear. METHODS: This multi-center cohort study consecutively recruited 5047 women from four areas of China who underwent BC screening. Breath samples were collected through standardized breath collection procedures. Volatile organic compound (VOC) markers were identified from a high-throughput breathomics analysis by the high-pressure photon ionization-time-of-flight mass spectrometry (HPPI-TOFMS). Diagnostic models were constructed using the random forest algorithm in the discovery cohort and tested in three external validation cohorts. RESULTS: A total of 465 (9.21%) participants were identified with BC. Ten optimal VOC markers were identified to distinguish the breath samples of BC patients from those of non-cancer women. A diagnostic model (BreathBC) consisting of 10 optimal VOC markers showed an area under the curve (AUC) of 0.87 in external validation cohorts. BreathBC-Plus, which combined 10 VOC markers with risk factors, achieved better performance (AUC = 0.94 in the external validation cohorts), superior to that of mammography and ultrasound. Overall, the BreathBC-Plus detection rates were 96.97% for ductal carcinoma in situ, 85.06%, 90.00%, 88.24%, and 100% for stages I, II, III, and IV BC, respectively, with a specificity of 87.70% in the external validation cohorts. CONCLUSIONS: This is the largest study on breath tests to date. Considering the easy-to-perform procedure and high accuracy, these findings exemplify the potential applicability of breath tests in BC screening.

Trispecific antibody targeting HIV-1 and T cells activates and eliminates latently-infected cells in HIV/SHIV infections.

Agents that can simultaneously activate latent HIV, increase immune activation and enhance the killing of latently-infected cells represent promising approaches for HIV cure. Here, we develop and evaluate a trispecific antibody (Ab), N6/αCD3-αCD28, that targets three independent proteins: (1) the HIV envelope via the broadly reactive CD4-binding site Ab, N6; (2) the T cell antigen CD3; and (3) the co-stimulatory molecule CD28. We find that the trispecific significantly increases antigen-specific T-cell activation and cytokine release in both CD4+ and CD8+ T cells. Co-culturing CD4+ with autologous CD8+ T cells from ART-suppressed HIV+ donors with N6/αCD3-αCD28, results in activation of latently-infected cells and their elimination by activated CD8+ T cells. This trispecific antibody mediates CD4+ and CD8+ T-cell activation in non-human primates and is well tolerated in vivo. This HIV-directed antibody therefore merits further development as a potential intervention for the eradication of latent HIV infection.

Cryptotanshinone-Doped Photothermal Synergistic MXene@PDA Nanosheets with Antibacterial and Anti-Inflammatory Properties for Wound Healing.

Humans are threatened by bacteria and other microorganisms, resulting in countless pathogen-related infections and illnesses. Accumulation of reactive oxygen species (ROS) in infected wounds activates strong inflammatory responses. The overuse of antibiotics has led to increasing bacterial resistance. Therefore, effective ROS scavenging and bactericidal capacity are essential and the advanced development of collaborative therapeutic techniques to combat bacterial infections is needed. Here, this work developes an MXene@polydopamine-cryptotanshinone (MXene@PDA-CPT) antibacterial nanosystem with excellent reactive oxygen and nitrogen species scavenging ability, which effectively inactivates drug-resistant bacteria and biofilms, thereby promoting wound healing. In this system, the adhesion of polydopamine nanoparticles to MXene produced a photothermal synergistic effect and free radical scavenging activity, presenting a promising antibacterial and anti-inflammatory strategy. This nanosystem causes fatal damage to bacterial membranes. The loading of cryptotanshinone further expanded the advantages of the system, causing a stronger bacterial killing effect and inflammation mitigatory effect with desired biosafety and biocompatibility. In addition, combining nanomaterials and active ingredients of traditional Chinese medicine, this work provides a new rationale for the future development of wound dressings, which contributes to eliminating bacterial resistance, delaying disease deterioration, and alleviating the pain of patients.

Revealing the Effect of Photothermal Therapy on Human Breast Cancer Cells: A Combined Study from Mechanical Properties to Membrane HSP70.

Hyperthermia-induced overexpression of heat shock protein 70 (HSP70) leads to the thermoresistance of cancer cells and reduces the efficiency of photothermal therapy (PTT). In contrast, cancer cell-specific membrane-associated HSP70 has been proven to activate antitumor immune responses. The dual effect of HSP70 on cancer cells inspires us that in-depth research of membrane HSP70 (mHSP70) during PTT treatment is essential. In this work, a PTT treatment platform for human breast cancer cells (MCF-7 cells) based on a mPEG-NH2-modified polydopamine (PDA)-coated gold nanorod core-shell structure (GNR@PDA-PEG) is developed. Using the force-distance curve-based atomic force microscopy (FD-based AFM), we gain insight into the PTT-induced changes in the morphology, mechanical properties, and mHSP70 expression and distribution of individual MCF-7 cells with high-resolution at the single-cell level. PTT treatment causes pseudopod contraction of MCF-7 cells and generates a high level of intracellular reactive oxygen species, which severely disrupt the cytoskeleton, leading to a decrease in cellular mechanical properties. The adhesion maps, which are recorded by aptamer A8 functional probes using FD-based AFM, reveal that PTT treatment causes a significant upregulation of mHSP70 expression and it starts to exhibit a partial aggregation distribution on the MCF-7 cell surface. This work not only exemplifies that AFM can be a powerful tool for detecting changes in cancer cells during PTT treatment but also provides a better view for targeting mHSP70 for cancer therapy.

Automatic prediction model for online diaphragm motion tracking based on optical surface monitoring by machine learning.

Background: The aim of this study was to establish a correlation model between external surface motion and internal diaphragm apex movement using machine learning and to realize online automatic prediction of the diaphragm motion trajectory based on optical surface monitoring. Methods: The optical body surface parameters and kilovoltage (kV) X-ray fluoroscopic images of 7 liver tumor patients were captured synchronously for 50 seconds. The location of the diaphragm apex was manually delineated by a radiation oncologist and automatically detected with a convolutional network model in fluoroscopic images. The correlation model between the body surface parameters and the diaphragm apex of each patient was developed through linear regression (LR) based on synchronous datasets before radiotherapy. Model 1 (M1) was trained with data from the first 30 seconds of the datasets and tested with data from the following 20 seconds of the datasets in the first fraction to evaluate the intra-fractional prediction accuracy. Model 2 (M2) was trained with data from the first 30 seconds of the datasets in the next fraction. The motion trajectory of the diaphragm apex during the following 20 seconds in the next fraction was predicted with M1 and M2, respectively, to evaluate the inter-fractional prediction accuracy. The prediction errors of the 2 models were compared to analyze whether the correlation model needed to be re-established. Results: The average mean absolute error (MAE) and root mean square error (RMSE) using M1 trained with automatic detection location for the first fraction were 3.12±0.80 and 3.82±0.98 mm in the superior-inferior (SI) direction and 1.38±0.24 and 1.74±0.32 mm in the anterior-posterior (AP) direction, respectively. The average MAE and RMSE of M1 versus M2 in the AP direction were 2.63±0.71 versus 1.28±0.48 mm and 3.26±0.90 versus 1.61±0.60 mm, respectively. The average MAE and RMSE of M1 versus M2 in the SI direction were 5.84±1.22 versus 3.37±0.43 mm and 7.22±1.45 versus 4.07±0.54 mm, respectively. The prediction accuracy of M2 was significantly higher than that of M1. Conclusions: This study shows that it is feasible to use optical body surface information to automatically predict the diaphragm motion trajectory. At the same time, it is necessary to establish a new correlation model for the current fraction before each treatment.

Experimental strategies to improve drug-target identification in mass spectrometry-based thermal stability assays.

Mass spectrometry (MS)-based thermal stability assays have recently emerged as one of the most promising solutions for the identification of protein-ligand interactions. Here, we have investigated eight combinations of several recently introduced MS-based advancements, including the Phase-Constrained Spectral Deconvolution Method, Field Asymmetric Ion Mobility Spectrometry, and the implementation of a carrier sample as improved MS-based acquisition approaches for thermal stability assays (iMAATSA). We used intact Jurkat cells treated with a commercially available MEK inhibitor, followed by heat treatment, to prepare a set of unfractionated isobarically-labeled proof-of-concept samples to compare the performance of eight different iMAATSAs. Finally, the best-performing iMAATSA was compared to a conventional approach and evaluated in a fractionation experiment. Improvements of up to 82% and 86% were demonstrated in protein identifications and high-quality melting curves, respectively, over the conventional approach in the proof-of-concept study, while an approximately 12% improvement in melting curve comparisons was achieved in the fractionation experiment.

Synthesis of ß-FeOOH/polyaniline heterogeneous catalyst for efficient photo-Fenton degradation of AOII dye.

Discharge of the untreated dye-containing wastewaters will induce water source pollution and further harm aquatic organisms. In this study, the akaganéite/polyaniline catalyst (ß-FeOOH/PANI, about 1.0 µm) could be successfully composed by polyaniline (PANI, (C6H7N)n, 200-300 nm) and akaganéite (ß-FeOOH, FeO(OH)1-xClx, less than 200 nm), according to the identification and characterization results of XRD, Ramon, FTIR, XPS, SEAD, EDS, and FESEM (or HRTEM). Due to PANI providing more photogenerated electrons, the ß-FeOOH/PANI composite (compared with ß-FeOOH) in photo-Fenton system had the more highly catalytic degradation capacity to Acid Orange II (AOII) under an optimal condition (7.5 mmol/L of H2O2 oxidant, 40 mg/L of AOII, 0.2 g/L of catalyst dosage, and pH 4.0). The AOII degradation kinetics could be well fitted by pseudo-first-order model. In photo-Fenton catalytic process of AOII dye, the ∙OH and h+ were the main reaction substances. The AOII in solutions could be gradually mineralized into non-toxic inorganic H2O molecule and CO2. The ß-FeOOH/PANI catalyst also had a good reusable ability of about 91.4% AOII degradation after 4 runs. These results can provide a reference for synthesis of catalyst used in photo-Fenton system and the applications in degradation removal of organic dye from wastewaters.

Loss of TTC17 promotes breast cancer metastasis through RAP1/CDC42 signaling and sensitizes it to rapamycin and paclitaxel.

BACKGROUND: Breast cancer (BC) metastasis is the leading cause of poor prognosis and therapeutic failure. However, the mechanisms underlying cancer metastasis are far from clear. METHODS: We screened candidate genes related to metastasis through genome-wide CRISPR screening and high-throughput sequencing of patients with metastatic BC, followed by a panel of metastatic model assays. The effects of tetratricopeptide repeat domain 17 (TTC17) on migration, invasion, and colony formation ability together with the responses to anticancer drugs were investigated in vitro and in vivo. The mechanism mediated by TTC17 was determined by RNA sequencing, Western blotting, immunohistochemistry, and immunofluorescence. The clinical significance of TTC17 was evaluated using BC tissue samples combined with clinicopathological data. RESULTS: We identified the loss of TTC17 as a metastasis driver in BC, and its expression was negatively correlated with malignancy and positively correlated with patient prognosis. TTC17 loss in BC cells promoted their migration, invasion, and colony formation capacity in vitro and lung metastasis in vivo. Conversely, overexpressing TTC17 suppressed these aggressive phenotypes. Mechanistically, TTC17 knockdown in BC cells resulted in the activation of the RAP1/CDC42 pathway along with a disordered cytoskeleton in BC cells, and pharmacological blockade of CDC42 abolished the potentiation of motility and invasiveness caused by TTC17 silencing. Research on BC specimens demonstrated reduced TTC17 and increased CDC42 in metastatic tumors and lymph nodes, and low TTC17 expression was linked to more aggressive clinicopathologic characteristics. Through screening the anticancer drug library, the CDC42 inhibitor rapamycin and the microtubule-stabilizing drug paclitaxel showed stronger inhibition of TTC17-silenced BC cells, which was confirmed by more favorable efficacy in BC patients and tumor-bearing mice receiving rapamycin or paclitaxel in the TTC17Low arm. CONCLUSIONS: TTC17 loss is a novel factor promoting BC metastasis, that enhances migration and invasion by activating RAP1/CDC42 signaling and sensitizes BC to rapamycin and paclitaxel, which may improve stratified treatment strategies under the concept of molecular phenotyping-based precision therapy of BC.

Differences in clinical characteristics and prognosis between breast neuroendocrine carcinoma and breast invasive ductal carcinoma: A multicentre population-based study from China.

AIM: We constructed a multicentre cohort in China to analyse the differences in clinical characteristics, treatment strategies and prognoses between breast neuroendocrine carcinoma (NEC) and invasive ductal carcinoma (IDC) of the breast. METHODS: All patients with early-stage breast cancer who attended three hospitals in Beijing from 2000 to 2018 were included in the study. We used propensity score matching to make a 1:3 match between NEC and IDC. RESULTS: After propensity score matching, 153 patients with IDC and 51 patients with NEC were analysed. Multivariate Cox regression showed that compared to patients with IDC, patients with NEC had a worse disease-free survival (HR = 2.94, 95% CI: 1.69-5.12, p < 0.001). CONCLUSION: NEC patients have a worse disease-free survival than IDC patients.

Erratum: Transcriptional Downregulation of miR-4306 serves as a New Therapeutic Target for Triple Negative Breast Cancer: Erratum.

[This corrects the article DOI: 10.7150/thno.30701.].