Music-induced emotion flow modeling by ENMI Network.

The relation between emotions and music is substantial because music as an art can evoke emotions. Music emotion recognition (MER) studies the emotions that music brings in the effort to map musical features to the affective dimensions. This study conceptualizes the mapping of music and emotion as a multivariate time series regression problem, with the aim of capturing the emotion flow in the Arousal-Valence emotional space. The Efficient Net-Music Informer (ENMI) Network was introduced to address this phenomenon. The ENMI was used to extract Mel-spectrogram features, complementing the time series data. Moreover, the Music Informer model was adopted to train on both time series music features and Mel-spectrogram features to predict emotional sequences. In our regression task, the model achieved a root mean square error (RMSE) of 0.0440 and 0.0352 in the arousal and valence dimensions, respectively, in the DEAM dataset. A comprehensive analysis of the effects of different hyperparameters tuning was conducted. Furthermore, different sequence lengths were predicted for the regression accuracy of the ENMI Network on three different datasets, namely the DEAM dataset, the Emomusic dataset, and the augmented Emomusic dataset. Additionally, a feature ablation on the Mel-spectrogram features and an analysis of the importance of the various musical features in the regression results were performed, establishing the effectiveness of the model presented herein.

Self-Assembly of Three-Dimensional Hyperbranched Magnetic Composites and Application in High-Turbidity Water Treatment.

In order to improve dispersibility, polymerization characteristics, chemical stability, and magnetic flocculation performance, magnetic Fe3O4 is often assembled with multifarious polymers to realize a functionalization process. Herein, a typical three-dimensional configuration of hyperbranched amino acid polymer (HAAP) was employed to assemble it with Fe3O4, in which we obtained three-dimensional hyperbranched magnetic amino acid composites (Fe3O4@HAAP). The characterization of the Fe3O4@HAAP composites was analyzed, for instance, their size, morphology, structure, configuration, chemical composition, charged characteristics, and magnetic properties. The magnetic flocculation of kaolin suspensions was conducted under different Fe3O4@HAAP dosages, pHs, and kaolin concentrations. The embedded assembly of HAAP with Fe3O4 was constructed by the N-O bond according to an X-ray photoelectron energy spectrum (XPS) analysis. The characteristic peaks of -OH (3420 cm-1), C=O (1728 cm-1), Fe-O (563 cm-1), and N-H (1622 cm-1) were observed in the Fourier transform infrared spectrometer (FTIR) spectra of Fe3O4@HAAP successfully. In a field emission scanning electron microscope (FE-SEM) observation, Fe3O4@HAAP exhibited a lotus-leaf-like morphological structure. A vibrating sample magnetometer (VSM) showed that Fe3O4@HAAP had a relatively low magnetization (Ms) and magnetic induction (Mr); nevertheless, the ferromagnetic Fe3O4@HAAP could also quickly respond to an external magnetic field. The isoelectric point of Fe3O4@HAAP was at 8.5. Fe3O4@HAAP could not only achieve a 98.5% removal efficiency of kaolin suspensions, but could also overcome the obstacles induced by high-concentration suspensions (4500 NTU), high pHs, and low fields. The results showed that the magnetic flocculation of kaolin with Fe3O4@HAAP was a rapid process with a 91.96% removal efficiency at 0.25 h. In an interaction energy analysis, both the UDLVO and UEDLVO showed electrostatic repulsion between the kaolin particles in the condition of a flocculation distance of <30 nm, and this changed to electrostatic attraction when the separation distance was >30 nm. As Fe3O4@ HAAP was employed, kaolin particles could cross the energy barrier more easily; thus, the fine flocs and particles were destabilized and aggregated further. Rapid magnetic separation was realized under the action of an external magnetic field.

Efficacy of Ultrasound-Guided Intercostal Nerve Block on Pain Management and Physiological Outcomes in Breast Cancer Mastectomy: A retrospective study.

To evaluate the efficacy of ultrasound-guided intercostal nerve block in managing pain and physiological responses in patients undergoing radical mastectomy for breast cancer. A retrospective study analyzed 120 patients scheduled to undergo radical mastectomy in our hospital between January 2022 and December 2023. Depending on the type of anesthesia received, participants were assigned to the experimental group (60 patients) to receive ultrasound-guided intercostal nerve block and intravenous general anesthesia, or the control group (60 patients) to receive intravenous general anesthesia only. Both groups will utilize patient-controlled intravenous analgesia (PCIA) postoperatively. We will monitor and compare hemodynamic parameters, SpO2, and bispectral index (BIS) at multiple time points, and assess postoperative pain, inflammatory markers, PCIA utilization, and adverse reaction incidence. Comparative analysis showed distinct trends in heart rate, mean arterial pressure (MAP), BIS, and SpO2 across various surgical stages between groups. Notably, MAP values were consistently higher and less variable in the experimental group during surgery (P < .05). Pain assessments at 4, 12, and 24 hours postoperatively in both quiet and coughing states revealed significantly milder pain in the experimental group (P < .05). Preoperative inflammatory markers (PGE2, TNF-α, IL-6, MCP-1) were similar between groups; however, 24 hours post-surgery, the experimental group showed significantly lower levels of PGE2, IL-6, and MCP-1 (P < .05). Sufentanil consumption during surgery and PCIA use were notably lower in the experimental group (P < .05). The experimental group also experienced fewer anesthesia-related adverse reactions (8.33%) compared to the control group (25.00%) (P < .05). Ultrasound-guided intercostal nerve block significantly improves hemodynamic stability, reduces postoperative inflammatory markers, lowers the need for sufentanil, and minimizes adverse reactions in patients undergoing radical mastectomy for breast cancer.

Enhancing local representation learning through global-local integration with functional connectivity for EEG-based emotion recognition.

Emotion recognition based on electroencephalogram (EEG) signals is crucial in understanding human affective states. Current research has limitations in extracting local features. The representation capabilities of local features are limited, making it difficult to comprehensively capture emotional information. In this study, a novel approach is proposed to enhance local representation learning through global-local integration with functional connectivity for EEG-based emotion recognition. By leveraging the functional connectivity of brain regions, EEG signals are divided into global embeddings that represent comprehensive brain connectivity patterns throughout the entire process and local embeddings that reflect dynamic interactions within specific brain functional networks at particular moments. Firstly, a convolutional feature extraction branch based on the residual network is designed to extract local features from the global embedding. To further improve the representation ability and accuracy of local features, a multidimensional collaborative attention (MCA) module is introduced. Secondly, the local features and patch embedded local embeddings are integrated into the feature coupling module (FCM), which utilizes hierarchical connections and enhanced cross-attention to couple region-level features, thereby enhancing local representation learning. Experimental results on three public datasets show that compared with other methods, this method improves accuracy by 4.92% on the DEAP, by 1.11% on the SEED, and by 7.76% on the SEED-IV, demonstrating its superior performance in emotion recognition tasks.

Cross-Modal Guiding Neural Network for Multimodal Emotion Recognition From EEG and Eye Movement Signals.

Multimodal emotion recognition research is gaining attention because of the emerging trend of integrating information from different sensory modalities to improve performance. Electroencephalogram (EEG) signals are considered objective indicators of emotions and provide precise insights despite their complex data collection. In contrast, eye movement signals are more susceptible to environmental and individual differences but offer convenient data collection. Conventional emotion recognition methods typically use separate models for different modalities, potentially overlooking their inherent connections. This study introduces a cross-modal guiding neural network designed to fully leverage the strengths of both modalities. The network includes a dual-branch feature extraction module that simultaneously extracts features from EEG and eye movement signals. In addition, the network includes a feature guidance module that uses EEG features to direct eye movement feature extraction, reducing the impact of subjective factors. This study also introduces a feature reweighting module to explore emotion-related features within eye movement signals, thereby improving emotion classification accuracy. The empirical findings from both the SEED-IV dataset and our collected dataset substantiate the commendable performance of the model, thereby confirming its efficacy.

Prediction of Epidermal Growth Factor Receptor Mutation Subtypes in Non-Small Cell Lung Cancer From Hematoxylin and Eosin-Stained Slides Using Deep Learning.

Accurate assessment of epidermal growth factor receptor (EGFR) mutation status and subtype is critical for the treatment of non-small cell lung cancer patients. Conventional molecular testing methods for detecting EGFR mutations have limitations. In this study, an artificial intelligence-powered deep learning framework was developed for the weakly supervised prediction of EGFR mutations in non-small cell lung cancer from hematoxylin and eosin-stained histopathology whole-slide images. The study cohort was partitioned into training and validation subsets. Foreground regions containing tumor tissue were extracted from whole-slide images. A convolutional neural network employing a contrastive learning paradigm was implemented to extract patch-level morphologic features. These features were aggregated using a vision transformer-based model to predict EGFR mutation status and classify patient cases. The established prediction model was validated on unseen data sets. In internal validation with a cohort from the University of Science and Technology of China (n = 172), the model achieved patient-level areas under the receiver-operating characteristic curve (AUCs) of 0.927 and 0.907, sensitivities of 81.6% and 83.3%, and specificities of 93.0% and 92.3%, for surgical resection and biopsy specimens, respectively, in EGFR mutation subtype prediction. External validation with cohorts from the Second Affiliated Hospital of Anhui Medical University and the First Affiliated Hospital of Wannan Medical College (n = 193) yielded patient-level AUCs of 0.849 and 0.867, sensitivities of 79.2% and 80.7%, and specificities of 91.7% and 90.7% for surgical and biopsy specimens, respectively. Further validation with The Cancer Genome Atlas data set (n = 81) showed an AUC of 0.861, a sensitivity of 84.6%, and a specificity of 90.5%. Deep learning solutions demonstrate potential advantages for automated, noninvasive, fast, cost-effective, and accurate inference of EGFR alterations from histomorphology. Integration of such artificial intelligence frameworks into routine digital pathology workflows could augment existing molecular testing pipelines.

Analysis of PIK3CA mutations in the primary and recurrent tumors of hormone receptor positive/human epidermal growth factor receptor 2 negative breast cancer.

OBJECTIVE: Our aim was to compare the PIK3CA mutation status in matched primary and recurrent tumors of hormone receptor positive/human epidermal growth factor receptor 2 negative (HR+/HER2-) breast cancer (BC) to gain insight into the optimization of patient selection and detection time for PIK3CA-targeted therapy. METHODS: The data were from 3035 patients with BC diagnosed at the Breast Disease Center, Peking University First Hospital, between January 2008 and December 2017. Matched primary and recurrent samples were profiled using amplification-refractory mutation system-polymerase chain reaction covering 11 mutational hotspots in PIK3CA. RESULTS: PIK3CA mutations were detected in 54.3% primary tumors and 48.6% corresponding recurrences. PIK3CA mutation was detected in 37.5% cases in the locoregional recurrent group and 40.0% of distant metastasis, without a statistical difference. Besides, PIK3CA mutations were concordant in 88.6% of the matched pairs. For patients treated with neoadjuvant chemotherapy, 100% concordance was observed. However, PIK3CA mutation was neither correlated with clinicopathological features nor associated with clinical outcomes. CONCLUSIONS: Mutations in PIK3CA in HR+/HER2- BC generally progressed to recurrent tumors. The high concordance rate of PIK3CA mutation status between primary tumors and corresponding recurrences suggests that the detection of primary tumors could be a substitute approach when recurrent samples are not easily obtainable.

A nomogram for predicting pathologic node negativity after neoadjuvant chemotherapy in breast cancer patients: a nationwide, multicenter retrospective cohort study (CSBrS-012).

Purpose: This study aimed to investigate the factors associated with pathologic node-negativity (ypN0) in patients who received neoadjuvant chemotherapy (NAC) to develop and validate an accurate prediction nomogram. Methods: The CSBrS-012 study (2010-2020) included female patients with primary breast cancer treated with NAC followed by breast and axillary surgery in 20 hospitals across China. In the present study, 7,711 eligible patients were included, comprising 6,428 patients in the primary cohort from 15 hospitals and 1,283 patients in the external validation cohort from five hospitals. The hospitals were randomly assigned. The primary cohort was randomized at a 3:1 ratio and divided into a training set and an internal validation set. Univariate and multivariate logistic regression analyses were performed on the training set, after which a nomogram was constructed and validated both internally and externally. Results: In total, 3,560 patients (46.2%) achieved ypN0, and 1,558 patients (20.3%) achieved pathologic complete response in the breast (bpCR). A nomogram was constructed based on the clinical nodal stage before NAC (cN), ER, PR, HER2, Ki67, NAC treatment cycle, and bpCR, which were independently associated with ypN0. The area under the receiver operating characteristic curve (AUC) for the training set was 0.80. The internal and external validation demonstrated good discrimination, with AUCs of 0.79 and 0.76, respectively. Conclusion: We present a real-world study based on nationwide large-sample data that can be used to effectively screen for ypN0 to provide better advice for the management of residual axillary disease in breast cancer patients undergoing NAC.

Reversible Fusion-Fission MXene Fiber-Based Microelectrodes for Target-Specific Gram-Positive and Gram-Negative Bacterium Discrimination.

Inaccurate or cumbersome clinical pathogen diagnosis between Gram-positive bacteria (G+) and Gram-negative (G-) bacteria lead to delayed clinical therapeutic interventions. Microelectrode-based electrochemical sensors exhibit the significant advantages of rapid response and minimal sample consumption, but the loading capacity and discrimination precision are weak. Herein, we develop reversible fusion-fission MXene-based fiber microelectrodes for G+/G- bacteria analysis. During the fissuring process, the spatial utilization, loading capacity, sensitivity, and selectivity of microelectrodes were maximized, and polymyxin B and vancomycin were assembled for G+/G- identification. The surface-tension-driven reversible fusion facilitated its reusability. A deep learning model was further applied for the electrochemical impedance spectroscopy (EIS) identification in diverse ratio concentrations of G+ and G- of (1:100-100:1) with higher accuracy (>93%) and gave predictable detection results for unknown samples. Meanwhile, the as-proposed sensing platform reached higher sensitivity toward E. coli (24.3 CFU/mL) and S. aureus (37.2 CFU/mL) in 20 min. The as-proposed platform provides valuable insights for bacterium discrimination and quantification.

Research on the Shale Reservoir Sensitivity by Using the Mineral Analysis Method.

Shale reservoirs have diverse mineral types, and analyzing the sensitivity of the mineral composition to shale pores is of great scientific and engineering significance. In this paper, first, X-ray diffraction (XRD) experiments on shale mineral compositions are carried out, and the characteristics of pore structure changes after shale mineral compositions interacted with external fluids (slick water and backflow fluid) are elucidated. Then, the effects of quartz, kaolinite, and pyrite on the pore structure and permeability of shale on the susceptibility to slick water are studied. The results show that (a) quartz and clay minerals are the dominant constituents of each core, with some cores containing minor amounts of plagioclase feldspar and rhodochrosite. (b) The composition of the shale changed significantly following the action of external fluids. The average quartz content of pure shale decreased from 31.62% to 29.1%. The average content of quartz in siliceous shale decreased from 36.53% to 33.5%. The average content of quartz in carbonaceous shale decreased from 9.15% to 8.05%. (c) Factors affecting the sensitivity of shale pore structure and permeability to slick water are mainly quartz, kaolinite, and pyrite. The contents of quartz, kaolinite, and pyrite decreased by an average of 5.1%, 4.6%, and 0.9%, respectively, after slick water action.

Primary lymphoma of the female genital tract masquerading as gynecological malignancy.

BACKGROUND: Primary lymphoma of the female genital tract (PLFGT) is a rare malignant tumor in the female reproductive system, with a low incidence and few clinical reports. The aim of this study is to report our institutional experience with this rare malignancy and emphasize the need for increasing the awareness about PLFGT presenting with gynecologic symptoms. METHODS: The medical records of patients diagnosed with PLFGT from March 2014 to November 2022 in the First Affiliated Hospital of Wannan Medical College were reviewed. Histological classification and staging were based on the World Health Organization and Ann Arbor systems, respectively. RESULTS: There were 13 patients with diagnosis of PLFGT and the median length of follow-up was 31 months (0-102 months). The main clinical symptoms included postmenopausal vaginal bleeding, pelvic mass and abdominal pain. Serum LDH increased in 10 patients and serum CA125 elevated in 2 patients. The tumor of ovarian or uterine presented as solid masses in CT or MRI, and ascites was rare. The histological subtypes were diffuse large B-cell (n = 12) and follicular (n = 1) lymphoma. Tumors were located in ovary (n = 8), uterus (n = 3), and cervix (n = 2). According to the Ann Arbor staging system, 6 cases were classified as stage II and 7 cases were classified as stage IV, respectively. A total of 10 patients underwent surgery. Combination chemotherapy was used in 10 patients. Eight patients had tumor-free survival, 1 patient had recurrent disease, 3 patients died and 1 patient lost to follow-up. The median survival time was 32 months (1-102 months). CONCLUSION: PLFGT usually presents as gynecological symptoms and solid masses in pelvis. Surgery or biopsy was the way to obtain the pathologic diagnosis, and combination chemotherapy is the efficient method for PLFGT. Making an accurate preoperative diagnosis is of paramount importance to avoid radical gynecologic surgery.

TSC2 nonsense mutation in angiomyolipoma with epithelial cysts: a case report and literature review.

Background: Angiomyolipoma with epithelial cysts (AMLEC) is an extremely rare subtype of kidney angiomyolipoma that contains epithelial-lined cysts. The most distinctive immunohistochemical feature of AMLEC is its immunoreactivity with melanocytic markers. AMLEC also has a distinct histological structure, which aids in its pathological diagnosis. To date 27 cases of AMLEC have been reported in 11 case series. However, the molecular biology underlying the pathogenesis of AMLEC remains unexplored. Case report: A 30-year-old female was diagnosed with AMLEC and underwent partial nephrectomy. Histologically, the cross-section of cystic tissue revealed a multilocular appearance, with some cysts containing thrombus-like material, and the wall thickness was approximately 0.2 ~ 0.3 cm. Additionally, the compact subepithelial cellular stroma showed strong and diffuse nuclear labeling for estrogen receptor, progesterone receptor, and CD10, as well as HMB45 and Melan A, which are markers of melanocytic differentiation. Furthermore, using a DNA targeted sequencing panel with next-generation sequencing, we identified a nonsense mutation in TSC Complex Subunit 2 (TSC2) gene, resulting in the formation of a premature termination codon. Moreover, the mutated genes found to be enriched in the PI3K-AKT pathway. The patient in this case had a favorable postoperative follow-up at 3 months. Conclusion: To the best of our knowledge, this study represents the first analysis of genotype mutations in AMLEC, providing valuable insights for future clinical practice. These findings have significant potential in guiding the understanding and management of AMLEC, paving the way for further research and advancements in the field.

Integrative analysis identifies cancer cell-intrinsic RARRES1 as a predictor of prognosis and immune response in triple-negative breast cancer.

Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor prognosis and limited treatment options. Although immune checkpoint inhibitors (ICIs) have been proven to improve outcomes in TNBC patients, the potential mechanisms and markers that determine the therapeutic response to ICIs remains uncertain. Revealing the relationship and interaction between cancer cells and tumor microenvironment (TME) could be helpful in predicting treatment efficacy and developing novel therapeutic agents. By analyzing single-cell RNA sequencing dataset, we comprehensively profiled cell types and subpopulations as well as identified their signatures in the TME of TNBC. We also proposed a method for quantitatively assessment of the TME immune profile and provided a framework for identifying cancer cell-intrinsic features associated with TME through integrated analysis. Using integrative analyses, RARRES1 was identified as a TME-associated gene, whose expression was positively correlated with prognosis and response to ICIs in TNBC. In conclusion, this study characterized the heterogeneity of cellular components in TME of TNBC patients, and brought new insights into the relationship between cancer cells and TME. In addition, RARRES1 was identified as a potential predictor of prognosis and response to ICIs in TNBC.

Exploring the Diagnostic and Prognostic Predictive Values of Ferroptosis- Related Markers in Lung Adenocarcinoma.

BACKGROUND: Lung Adenocarcinoma (LUAD), a common and aggressive form of lung cancer, poses significant treatment challenges due to its low survival rates. AIM: To better understand the role of ferroptosis driver genes in LUAD, this study aimed to explore their diagnostic and prognostic significance, as well as their impact on treatment approaches and tumor immune function in LUAD. METHOD: To accomplish the defined goals, a comprehensive methodology incorporating both in silico and wet lab experiments was employed. A comprehensive analysis was conducted on a total of 233 ferroptosis driver genes obtained from the FerrDB database. Utilizing various TCGA databases and the RT-qPCR technique, the expression profiles of 233 genes were examined. Among them, TP53, KRAS, PTEN, and HRAS were identified as hub genes with significant differential expression. Notably, TP53, KRAS, and HRAS exhibited substantial up-regulation, while PTEN demonstrated significant down-regulation at both the mRNA and protein levels in LUAD samples. The dysregulation of hub genes was further associated with poor overall survival in LUAD patients. Additionally, targeted bisulfite-sequencing (bisulfite-seq) analysis revealed aberrant promoter methylation patterns linked to the dysregulation of hub genes. RESULT & DISCUSSION: Furthermore, hub genes were found to participate in diverse oncogenic pathways, highlighting their involvement in LUAD tumorigenesis. By leveraging the diagnostic and prognostic potential of ferroptosis driver hub genes (TP53, KRAS, PTEN, and HRAS), significant advancements can be made in the understanding and management of LUAD pathogenesis. CONCLUSION: Therapeutic targeting of these genes using specific drugs holds great promise for revolutionizing drug discovery and improving the overall survival of LUAD patients.

Axillary lymph node dissection in triple-negative or HER2-positive breast cancer patients with clinical N2 achieving pathological complete response after neoadjuvant therapy: Is it necessary?

AIM: This study aims to identify suitable candidates for axillary sentinel lymph node biopsy (SLNB) or targeted axillary dissection (TAD) among clinical N2 (cN2) triple-negative (TN) or HER2 positive (HER2+）breast cancer patients following neoadjuvant therapy（NAT）. BACKGROUND: Despite the substantial axillary burden in cN2 breast cancer patients, high pathological response rates can be achieved with NAT in TN or HER2+ subtypes, thus enabling potential downstaging of axillary surgery. METHODS: A retrospective analysis was conducted on data from the CSBrS-012 study, screening 709 patients with initial cN2, either HER2+ or TN subtype, from January 1, 2010 to December 31, 2020. The correlation between axillary pathologic complete response (pCR) (yPN0) and breast pCR was examined. RESULTS: Among the 177 cN2 patients who achieved breast pCR through NAT, 138 (78.0 %) also achieved axillary pCR. However, in the 532 initial clinical N2 patients who did not achieve breast pCR, residual axillary lymph node metastasis persisted in 77.4 % (412/532) of cases. The relative risk of residual axillary lymph node metastasis in patients who did not achieve breast pCR was 12.4 (8.1-19.1), compared to those who did achieve breast pCR, P < 0.001. CONCLUSION: For cN2 TN or HER2+ breast cancer patients who achieve breast pCR following NAT, consideration could be given to downstaging and performing an axillary SLNB or TAD.

The association of systemic inflammatory biomarkers with non-alcoholic fatty liver disease: a large population-based cross-sectional study.

Purpose: The aim of this study was to explore the relationship between non-alcoholic fatty liver disease (NAFLD) and the two blood inflammatory markers including the systemic immune-inflammation (SII) index, and the system inflammation response index (SIRI). Methods: The National Health and Nutrition Examination Survey data between the year of 2017-2018 was used for this cross-sectional study. In order to analyze the association of SII index, and SIRI and risk of NAFLD, we used multivariable logistic regression models, restricted cubic spline (RCS) plot, and subgroup analysis to analyze the data. Results: In total, there were 1,199 individuals who participated in the survey. As shown by the RCS plot, SII index, and SIRI were linked with NAFLD risk in a U-shaped pattern. With regard to known confounding variables, when comparing the lowest quartile, the odds ratio with 95 % confidence interval for prevalence of NAFLD across the quartiles of SII index and SIRI were (0.89 (0.57, 1.41), 0.56 (0.35, 0.89) and 1.01 (0.64, 1.59)), and (0.77 (0.48, 1.23), 0.79 (0.50, 1.24) and 0.94 (0.60, 1.47)), respectively. Additionally, SII index, and SIRI and NAFLD risk also were U-curve correlated among the participants in age ≥60 years, female, without hypertension, and BMI of ≥30 kg/m2. Conclusions: There was a U-shaped association of SII index and SIRI with prevalence of NAFLD, indicating that SII index and SIRI should be monitored dynamically.

Corrigendum: A novel feature fusion network for multimodal emotion recognition from EEG and eye movement signals.

[This corrects the article DOI: 10.3389/fnins.2023.1234162.].

Preparation and Application of Amino-Terminated Hyperbranched Magnetic Composites in High-Turbidity Water Treatment.

In order to separate the colloidal in high-turbidity water, a kind of magnetic composite (Fe3O4/HBPN) was prepared via the functional assembly of Fe3O4 and an amino-terminal hyperbranched polymer (HBPN). The physical and chemical characteristics of Fe3O4@HBPN were investigated by different means. The Fourier Transform infrared spectroscopy (FTIR) spectra showed that the characteristic absorption peaks positioned at 1110 cm-1, 1468 cm-1, 1570 cm-1 and 1641 cm-1 were ascribed to C-N, H-N-C, N-H and C=O bonds, respectively. The shape and size of Fe3O4/HBPN showed a different and uneven distribution; the particles clumped together and were coated with an oil-like film. Energy-dispersive spectroscopy (EDS) displayed that the main elements of Fe3O4/HBPN were C, N, O, and Fe. The superparamagnetic properties and good magnetic response were revealed by vibrating sample magnetometer (VSM) analysis. The characteristic diffraction peaks of Fe3O4/HBPN were observed at 2θ = 30.01 (220), 35.70 (311), 43.01 (400), 56.82 (511), and 62.32 (440), which indicated that the intrinsic phase of magnetite remained. The zeta potential measurement indicated that the surface charge of Fe3O4/HBPN was positive in the pH range 4-10. The mass loss of Fe3O4/HBPN in thermogravimetric analysis (TGA) proved thermal decomposition. The -C-NH2 or -C-NH perssad of HBPN were linked and loaded with Fe3O4 particles by the N-O bonds. When the Fe3O4/HBPN dosage was 2.5 mg/L, pH = 4-5, the kaolin concentration of 1.0 g/L and the magnetic field of 3800 G were the preferred reaction conditions. In addition, a removal efficiency of at least 86% was reached for the actual water treatment. Fe3O4/HBPN was recycled after the first application and reused five times. The recycling efficiency and removal efficiency both showed no significant difference five times (p > 0.05), and the values were between 84.8% and 86.9%.

A multicenter study of the clinicopathological characteristics and a risk prediction model of early-stage breast cancer with hormone receptor-positive/human epidermal growth factor receptor 2-low expression.

BACKGROUND: In light of the significant clinical benefits of antibody-drug conjugates in clinical trials, the human epidermal growth factor receptor 2 (HER2)-low category in breast cancers has gained increasing attention. Therefore, we studied the clinicopathological characteristics of Chinese patients with hormone receptor (HR)-positive/HER2-low early-stage breast cancer and developed a recurrence risk prediction model. METHODS: Female patients with HR-positive/HER2-low early-stage breast cancer treated in 29 hospitals of the Chinese Society of Breast Surgery (CSBrS) from Jan 2015 to Dec 2016 were enrolled. Their clinicopathological data and prognostic information were collected, and machine learning methods were used to analyze the prognostic factors. RESULTS: In total, 25,096 patients were diagnosed with breast cancer in 29 hospitals of CSBrS from Jan 2015 to Dec 2016, and clinicopathological data for 6486 patients with HER2-low early-stage breast cancer were collected. Among them, 5629 patients (86.79%) were HR-positive. The median follow-up time was 57 months (4, 76 months); the 5-year disease-free survival (DFS) rate was 92.7%, and the 5-year overall survival (OS) rate was 97.7%. In total, 412 cases (7.31%) of metastasis were observed, and 124 (2.20%) patients died. Multivariate Cox regression analysis revealed that T stage, N stage, lymphovascular thrombosis, Ki-67 index, and prognostic stage were associated with recurrence and metastasis ( P <0.05). A recurrence risk prediction model was established using the random forest method and exhibited a sensitivity of 81.1%, specificity of 71.7%, positive predictive value of 74.1%, and negative predictive value of 79.2%. CONCLUSION: Most of patients with HER2-low early-stage breast cancer were HR-positive, and patients had favorable outcome; tumor N stage, lymphovascular thrombosis, Ki-67 index, and tumor prognostic stage were prognostic factors. The HR-positive/HER2-low early-stage breast cancer recurrence prediction model established based on the random forest method has a good reference value for predicting 5-year recurrence events. REGISTRITATION: ChiCTR.org.cn, ChiCTR2100046766.