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Purpose: In breast cancer (BC) patients with clinical axillary lymph node metastasis (cN+) undergoing neoadjuvant therapy (NAT), precise axillary lymph node (ALN) assessment dictates therapeutic strategy. There is a critical demand for a precise method to assess the axillary lymph node (ALN) status in these patients. Materials and methods: A retrospective analysis was conducted on 160 BC patients undergoing NAT at Fujian Medical University Union Hospital. We analyzed baseline and two-cycle reassessment dynamic contrast-enhanced MRI (DCE-MRI) images, extracting 3668 radiomic and 4096 deep learning features, and computing 1834 delta-radiomic and 2048 delta-deep learning features. Light Gradient Boosting Machine (LightGBM), Support Vector Machine (SVM), RandomForest, and Multilayer Perceptron (MLP) algorithms were employed to develop risk models and were evaluated using 10-fold cross-validation. Results: Of the patients, 61 (38.13 %) achieved ypN0 status post-NAT. Univariate and multivariable logistic regression analyses revealed molecular subtypes and Ki67 as pivotal predictors of achieving ypN0 post-NAT. The SVM-based “Data Amalgamation” model that integrates radiomic, deep learning features, and clinical data, exhibited an outstanding AUC of 0.986 (95 % CI: 0.954–1.000), surpassing other models. Conclusion: Our study illuminates the challenges and opportunities inherent in breast cancer management post-NAT. By introducing a sophisticated, SVM-based “Data Amalgamation” model, we propose a way towards accurate, dynamic ALN assessments, offering potential for personalized therapeutic strategies in BC.

Abstract Soft robots have the advantage of adaptability and flexibility in various scenarios and tasks due to their inherent flexibility and mouldability, which makes them highly promising for real‐world applications. The development of electronic skin (E‐skin) perception systems is crucial for the advancement of soft robots. However, achieving both exteroceptive and proprioceptive capabilities in E‐skins, particularly in terms of decoupling and classifying sensing signals, remains a challenge. This study presents an E‐skin with mixed electronic and ionic conductivity that can simultaneously achieve exteroceptive and proprioceptive, based on the resistance response of conductive hydrogels. It is integrated with soft robots to enable state perception, with the sensed signals further decoded using the machine learning model of decision trees and random forest algorithms. The results demonstrate that the newly developed hydrogel sensing system can accurately predict attitude changes in soft robots when subjected to varying degrees of pressing, hot pressing, bending, twisting, and stretching. These findings that multifunctional hydrogels combine with machine learning to decode signals may serve as a basis for improving the sensing capabilities of intelligent soft robots in future advancements.

Abstract Background Male breast cancer constitutes a minority of breast cancer diagnoses, yet its incidence has been on the rise in recent decades. However, elderly male breast cancer patients have been inadequately represented in clinical trials, posing challenges in treatment decisions. This study seeks to clarify the efficacy of chemotherapy in this demographic and identify the population most likely to benefit from such intervention. Methods We conducted a retrospective analysis using the Surveillance, Epidemiology, and End Results (SEER) database, encompassing a total of 1900 male breast cancer patients aged 70 years or older. Among them, 1652 were categorized in the no-chemotherapy group, while 248 were in the chemotherapy group. A multifactorial logistic regression model was employed to investigate the determinants influencing the administration of chemotherapy in elderly male breast cancer patients. Additionally, the multivariate Cox proportional hazards regression model was applied to identify factors associated with outcomes, with overall survival (OS) as the primary endpoint. Results Multivariate logistic regression analysis revealed that grade, tumor size, and nodal status were robust predictors for elderly male breast cancer patients receiving chemotherapy. Furthermore, the multivariate analysis demonstrated that chemotherapy conferred benefits compared to the no-chemotherapy group (HR = 0.822, 95% CI: 0.682–0.991, p = 0.040). Stratified analyses indicated that individuals with N+, poorly/undifferentiated grade, and stage II/III disease could derive benefits from chemotherapy. Upon further investigation of progesterone receptor (PR) positive patients, it was found that only stage III patients experienced significant benefits from chemotherapy (HR = 0.571, 95% CI: 0.372–0.875, p = 0.010). Conversely, in PR negative patients, both stage II (HR = 0.201, 95% CI: 0.051–0.792, p = 0.022) and stage III patients (HR = 0.242, 95% CI: 0.060–0.972, p = 0.046) derived benefits from chemotherapy. Conclusion Adjuvant chemotherapy may benefit certain elderly male breast cancer patients, specifically those with positive lymph node status, poorly/undifferentiated grade, and PR-positive in stage III, as well as PR-negative expression in stage II/III. Given favorable physical tolerance, it is advisable not to hastily dismiss chemotherapy for these elderly male breast cancer patients.

Near-infrared (NIR) persistent luminescence nanoparticles (PLNPs) have inherent advantages for high-sensitivity bioimaging due to the separation of excitation and emission light. However, the single-wavelength emission of NIR PLNPs for bioimaging limits their use in photodynamic therapy (PDT). Herein, a biological window excited up-conversion (UC) PLNPs, Zn3Ga2SnO8:Cr3+,Yb3+,Ho3+ (ZGS), was reported for bioimaging and PDT. ZGS exhibits NIR persistent luminescence (PersL) after red LED excitation and visible UCL under 980 nm excitation. The NIR PersL is designed for in vivo bioimaging; the visible UCL is used to activate photosensitizer (PS) to generate reactive oxygen species (ROS) for PDT. The dual-functional ZGS with UCL and PersL provides an effective method for bioimaging and PDT, which is expected to further promote the application of PLNPs in the integration of efficient diagnosis and treatment.

Abstract A novel Frequency and Polarisation Selective Surface (FPSS) is proposed, which separates two adjacent bands with a narrow transition zone by the staggered separation scheme and is suitable for atmospheric remote sensing. The traditional FSS is transparent in a particular frequency band for both the TE and TM polarisations, while it is opaque in another band for both orthogonal polarisations. The FPSS is introduced in a new splitting scheme that operates above 300 GHz. The channel 420–430 GHz of the TE polarisation and the channel 360–400 GHz of the TM polarisation transmit in the FPSS. In contrast, the band 360–400 GHz of the TE polarisation and the channel 420–430 GHz of the TM polarisation are reflected. The water vapour and the oxygen profiles are detected by the 380 GHz band and the 425 GHz band, respectively. The insertion loss is lower than 1 dB, and the reflection band rejection is superior to 10 dB in the experiment, which determine the sensitivities of the bright temperature by 1.5 (RMS K). The scattered wave of the FPSS is calculated through the far field pattern, the maximum of which is about 5%. The side effect of the scattered wave is able to be ignored in the optical path.

Abstract Background Small tyrosine kinase inhibitors (TKIs) show activity against breast cancer brain metastases (BCBM) of the human epidermal growth factor receptor 2 (HER2)‐positive subtype. This meta‐analysis aimed to objectively explore the efficacy and safety of TKIs. Methods Electronic databases were searched for relevant clinical trials. We conducted a pairwise meta‐analysis, pooled analysis, and estimated summary survival curves to compare survival outcomes following TKIs therapy for BCBM patients using Stata version 16.0 or R x64 4.0.5. Results Thirteen clinical trials involving 987 HER2‐positive BCBM patients were analyzed. A trend of longer progression‐free survival (PFS) was observed in the TKI‐containing arm compared to the non‐TKI‐containing arm (hazard ratio = 0.64, 95% confidence interval [CI]: 0.35–1.15, p = 0.132), although the difference is not statistically significant. Summary survival curves reported the summary median PFS and overall survival were 7.9 months and 12.3 months. Subgroup analysis revealed that TKIs combined with capecitabine (TKI + Cap) regimens resulted in improved survival outcomes. Tucatinib may be more effective in BCBM patients. The main grade 3–5 adverse events (AEs) were diarrhea (22%, 95% CI: 14%–32%), neutropenia (11%, 95% CI: 5%–18%), hepatic toxicity (7%, 95% CI: 1%–16%), and sensory neuropathy (6%, 95% CI: 2%–12%). Conclusion TKIs therapy improved the survival outcomes of HER2‐positive BCBM patients, especially when combined with capecitabine and tolerable AEs. We also identified the clinical value of tucatinib, which appears to be the most favorable TKI drug for BCBM patients.

Abstract Background To investigate the anti-inflammatory and antioxidative effects of gallic acid (GA) on human corneal epithelial cells (HCECs) and RAW264.7 macrophages as well as its therapeutic effects in an experimental dry eye (EDE) mouse model. Methods A cell counting kit-8 (CCK-8) assay was used to test the cytotoxicity of GA. The effect of GA on cell migration was evaluated using a scratch wound healing assay. The anti-inflammatory and antioxidative effects of GA in vitro were tested using a hypertonic model (HCECs) and an inflammatory model (RAW264.7 cells). The in vivo biocompatibility of GA was detected by irritation tests in rabbits, whereas the preventive and therapeutic effect of GA in vivo was evaluated using a mouse model of EDE. Results In the range of 0–100 μM, GA showed no cytotoxicity in RAW264.7 cells or HCECs and did not delay the HCECs monolayer wound healing within 24 h. Ocular tolerance to GA in the in vivo irritation test was good after seven days. In terms of antioxidative activity, GA significantly reduced the intracellular reactive oxygen species (ROS) in lipopolysaccharide (LPS) activated RAW264.7 macrophages and HCECs exposed to hyperosmotic stress. Furthermore, after pre-treatment with GA, the expression levels of nuclear factor E2-related factor 2 (Nrf2), heme oxygenase-1 (HO-1), and NADPH quinone oxidoreductase-1 (NQO-1) were significantly upregulated in RAW264.7 macrophages. GA also exhibits excellent anti-inflammatory properties. This is mainly demonstrated by the ability of GA to effectively downregulate the nuclear transcription factor-κB (NF-κB) pathway in LPS-activated RAW264.7 macrophages and to reduce inflammatory factors, such as nitric oxide (NO), interleukin 6 (IL-6), and tumor necrosis factor alpha (TNF-α). In vivo efficacy testing results in a mouse model of EDE showed that GA can effectively prevent and inhibit the apoptosis of corneal epithelial cells (CECs), reduce inflammatory factors in the cornea and conjunctiva as well as protect goblet cells. Conclusion In vitro and in vivo results indicate that GA possesses potent anti-inflammatory and antioxidative properties with no apparent cytotoxicity within the range of 0–100 μM. It is a promising eye drop formulation for the effective prevention and treatment of dry eye disease (DED).

BackgroundPrimary breast lymphoma (PBL) is a rare disease whose epidemiological features, treatment principles, and factors used for the patients’ prognosis remain controversial. ObjectiveThe aim of this study was to explore the epidemiology of PBL and to develop a better model based on machine learning to predict the prognosis for patients with primary breast lymphoma. MethodsThe annual incidence of PBL was extracted from the surveillance, epidemiology, and end results database between 1975 and 2019 to examine disease occurrence trends using Joinpoint software (version 4.9; National Cancer Institute). We enrolled data from 1251 female patients with primary breast lymphoma from the surveillance, epidemiology, and end results database for survival analysis. Univariable and multivariable analyses were performed to explore independent prognostic factors for overall survival and disease-specific survival of patients with primary breast lymphoma. Eight machine learning algorithms were developed to predict the 5-year survival of patients with primary breast lymphoma. ResultsThe overall incidence of PBL increased drastically between 1975 and 2004, followed by a significant downward trend in incidence around 2004, with an average annual percent change (AAPC) of −0.8 (95% CI −1.1 to −0.6). Disparities in trends of PBL exist by age and race. The AAPC of the 65 years or older cohort was about 1.2 higher than that for the younger than 65 years cohort. The AAPC of White patients is 0.9 (95% CI 0.0-1.8), while that of Black patients was significantly higher at 2.1 (95% CI −2.5 to 6.9). We also identified that the risk of death from PBL is multifactorial and includes patient factors and treatment factors. Survival analysis revealed that the patients diagnosed between 2007 and 2015 had a significant risk reduction of mortality compared to those diagnosed between 1983 and 1990. The gradient booster model outperforms other models, with 0.752 for sensitivity and 0.817 for area under the curve. The important features established with the gradient booster model were the year of diagnosis, age, histologic type, and primary site, which were the 4 most relevant variables to explain 5-year survival status. ConclusionsThe incidence of PBL started demonstrating a tendency to decrease after 2004, which varied by age and race. In recent years, the prognosis of patients with primary breast lymphoma has been remarkably improved. The gradient booster model had a promising performance. This model can help clinicians identify the early prognosis of patients with primary breast lymphoma and therefore improve the clinical outcome by changing management strategies and patient health care.

The antioxidant activity of curcumin has been extensively investigated for years. However, its molecular function mechanism remained unclear. Our preliminary study showed that curcumin downregulated miR-22-3p expression. This study aimed to address whether miR-22-3p mediated the antioxidant activity of curcumin and the possible action mechanism. The results showed that miR-22-3p repression increased the total cellular antioxidant capacity and enhanced the endogenous antioxidant enzyme system of LO2 cells. In addition, miR-22-3p-deteriorated cellular antioxidant capacity was prevented by curcumin pretreatment. Moreover, miR-22-3p inhibition significantly improved mitochondrial function and biogenesis. Further investigation demonstrated that a mitochondrial key regulator, the cardiolipin synthase gene (CRLS1), was targeted and downregulated by miR-22-3p. CRLS1 overexpression also significantly improved cellular antioxidant capacity and enhanced mitochondrial function and biogenesis in LO2 cells. Taken together, all these data suggested that miR-22-3p modulated the antioxidant effect of curcumin via targeting CRLS1, which may provide novel insights into miRNA-mediated antioxidant mechanism of curcumin.

Abstract Purpose We aimed to analysis the impact of chemotherapy and establish prediction models of prognosis in early elderly triple negative breast cancer (eTNBC) by using machine learning. Methods We enrolled 4,696 patients in SEER Database who were 70 years or older, diagnosed with primary early TNBC(larger than 5 mm), from 2010 to 2016. The propensity-score matched method was utilized to reduce covariable imbalance. Univariable and multivariable analyses were used to compare breast cancer-specific survival(BCSS) and overall survival(OS). Nine models were developed by machine learning to predict the 5-year OS and BCSS for patients received chemotherapy. Results Compared to matched patients in no-chemotherapy group, multivariate analysis showed a better survival in chemotherapy group. Stratified analyses by stage demonstrated that patients with stage II and stage III other than stage I could benefit from chemotherapy. Further investigation in stage II found that chemotherapy was a better prognostic indicator for patients with T2N0M0 and stage IIb, but not in T1N1M0. Patients with grade III could achieve a better survival by receiving chemotherapy, but those with grade I and II couldn’t. With 0.75 in 5-year BCSS and 0.81 in 5-year OS for AUC, the LightGBM outperformed other algorithms. Conclusion For early eTNBC patients with stage I, T1N1M0 and grade I-II, chemotherapy couldn’t improve survival. Therefore, de-escalation therapy might be appropriate for selected patients. The LightGBM is a trustful model to predict the survival and provide precious systemic treatment for patients received chemotherapy.

The composites with multiple types of nano-carbon fillers have better electrical conductivity and piezoresistive properties as compared with composites with a single type of nano-carbon fillers. As previously reported, the nano-carbon fillers with various aspect ratios, such as carbon nanotube (CNT) and carbon black (CB), have synergistic enhanced effects on the piezoresistive performance of composite sensors. However, most of the works that have been reported are experimental investigations. The efficient and usable numerical simulation investigation needs to be further developed. In this study, based on an integrated 3D statistical resistor network model, a numerical simulation model was created to calculate the piezoresistive behavior of the CNT/CB/ Polyvinylidene Fluoride (PVDF) composite. This model also takes into account the tunneling effect between nearby nano-fillers. It is found from numerical simulation results that the piezoresistive sensitivity of composite simulation cells can be influenced by the fraction of CNT and CB. In the case that the CNT content is 0.073 wt.%, the best force-electrical piezoresistive sensitivity can be achieved when the CB loading is up to 0.2 wt.%. To verify the validity of the simulation model, the previous experimental investigation results are also compared. The experimental results confirm the validity of the model. The investigation is valuable and can be utilized to design a strain sensor for this nano-composite with increased sensitivity.

Abstract The synergistic effects of surface treatment and interleaf on the interlaminar mechanical properties of glass fiber-aluminum laminates were studied. Aluminum sheets were treated with alkaline etching. Meanwhile, a graphene oxide (GO) interleaf was introduced between the aluminum sheet and the glass fiber-reinforced epoxy composite. Double cantilever beam and end-notched flexure tests were employed to evaluate the interlaminar fracture toughness of the glass fiber-aluminum laminates. The obtained results show that the toughening efficiency of the interleaf is dependent on the aluminum surface characteristics as well as the GO loading. Further comparison reveals that the highest mode-I and mode-II fracture toughnesses are obtained in the specimens with alkali etching treatment and addition of GO interleaf with 0.5 wt% of GO loading, which are 510% and 381% higher in comparison to the plain specimen. Fracture surfaces were observed to further uncover the reinforcement mechanisms.

We conducted molecular dynamics (MD) simulations of tension and compression along the direction and MD simulations of compression along the and directions on nanolaminated graphene/Cu (NGCu) composites to investigate the effects of the incorporated graphene and the deformation mechanisms related to the loading direction. The deformation behavior and the defect structures were found to be strongly dependent on the loading conditions. An asymmetric tension-compression deformation behavior was thus found in graphene/Cu nanolaminates under the loading, which was dominated by stacking faults and deformation twins formed by dislocation slide under tension and compression, respectively. High density and ordered nanotwins were formed at the graphene/Cu interfaces. Two different formation mechanisms of the twins were found under the compression, and the nucleated twins were easy to be thickened with the assistance of the graphene wrinkles. Multiple twins were formed under the compression by the dislocation cross-slip. This study provides a way to introduce graphene reinforcement and twin boundary to Cu matrix composites and design nanotwinned graphene/Cu composites with excellent mechanical performance. Keywords: Deformation Mechanisms, Molecular Dynamics, Graphene/Cu Composites, Interface, Twin

Background Breast surgery for stage IV breast cancer remains controversial. The aim of this study was to investigate the impact of breast surgery on survival of stage IV breast cancer patients based on the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2015. Methods In total, 13,034 patients were selected and divided into surgery and non-surgery groups. Univariate and multivariable analyses were conducted to determine factors related to survival. Propensity score matching method was utilized to achieve balanced covariates across different groups. One-to-one (1:1) PSM was conducted to construct a matched sample consisting of pairs of surgery and non-surgery subjects. Breast cancer-specific survival (BCSS) and overall survival (OS) of the two groups were assessed by Kaplan–Meier plots and Cox proportional hazard regression models. Stratified analysis according to different variables was also performed. Results Patients treated with breast surgery were more likely to be younger, smaller tumor size, more advanced nodal status, higher histology grade and higher proportion of bone-only metastasis. Those who received chemotherapy and radiotherapy also tended to be treated with surgery. After adjustment for potential confounders, breast surgery group exhibited a better survival both in BCSS (HR = 0.557, 95% CI [0.523–0.594], p

Asymmetric modes competition in Cerenkov devices were studied with a view to developing a novel method to suppress modes competition, based on loading of the slow-wave structure (SWS) with an anisotropic medium. Due to differences in the field distribution between the asymmetric and symmetric modes, the asymmetric modes are susceptible to significant attenuation in anisotropic media with an appropriate imaginary part for the azimuthal permittivity. In contrast, the symmetric modes, such as the TM01 mode, incur no such losses. Using the EH11 mode as an example, the quality factor obtained from experiments involving the SWS loaded with an anisotropic medium was reduced by approximately 90% compared with that for a copper SWS. The attenuation was sufficiently high that the electromagnetic fields for the asymmetric modes were barely established, indicating that the suppression technique was highly effective. The approach provides a feasible way to eliminate asymmetric modes in high-power microwave (HPM) sources and may lead to a range of new applications in HPM systems.

Carbon nanotube (CNT)/epoxy resin (EP) conductive composite can be obtained by solidifying the mixture of CNT and EP at specific temperature. The conductivity of the CNT/EP composite rises as the CNT content increases. It has been proven that the electrical resistance of a CNT/EP film varies when it experiences tension or compression. Therefore, the current research focuses on the design of strain sensors, based on the piezoresistivity of CNT/EP composite. In this article, an efficient method used to fabricate CNT/EP sensors is introduced in detail. One main novelty of the present method is that it provides an easy process to install metal electrodes for each piece of CNT/EP film. Another importance of the method is that it tackles the obstacles on the way to bulk production. A cantilever beam system was used to test the sensors fabricated through the self-developed process. The experimental results show that the sensors have consistent properties, and their gauge factors are much higher than that of typical foil strain gauges. [ABSTRACT FROM AUTHOR]