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Abstract Background Hormone receptor‐positive (HR+)/human epidermal growth factor receptor 2‐positive (HER2+) breast cancer exhibits considerable heterogeneity, and it is of great interest whether patients with premenopausal HR+/HER2+ breast cancer treated with trastuzumab can benefit from ovarian function suppression (OFS) therapy similarly to HR+/HER2‐ breast cancer. Here, we conducted a real‐world study in this population to identify both who would derive substantial benefits from the addition of OFS and clinicopathological factors with potential prognostic value. Methods Multicenter data from 253 premenopausal patients with HR+/HER2+ early‐stage breast cancer who received trastuzumab from October 2009 to October 2018 were retrospectively included. The Kaplan–Meier method was used for survival analysis, while the log‐rank test was used to compare the survival rates. Univariate and multifactor Cox regression analyses were performed to analyze the independent risk factors affecting invasive disease‐free survival (IDFS). Results After a median follow‐up of 98.50 months, compared with tamoxifen/toremifene alone, tamoxifen/toremifene/aromatase inhibitors plus OFS demonstrated significant benefits in the overall study population (HR = 0.289, 95% CI: 0.100–0.835, p = 0.022, 8‐year IDFS rate: 90.78% vs. 95.54%), especially in the lymph node‐positive subgroup and age ≤40 years subgroup. Age ≤40 years, histological grade >2, lymph node involvement, PR ≤50%, and tamoxifen alone were independent prognostic factors. Conclusions For premenopausal HR+ breast cancer patients, HER2 positivity alone is an indication for the addition of OFS in adjuvant endocrine therapy. Age, histological grade, lymph node status, the expression of PR, and OFS treatment were independent prognostic factors in this population.

Abstract In recent decades, using circulating tumor cell (CTC), circulating tumor DNA (ctDNA), circulating tumor RNA (ctRNA), exosomes and etc. as liquid biomarkers has received enormous attention in various tumors, including breast cancer (BC). To date, efforts in the area of liquid biopsy predominantly focus on the analysis of blood-based markers. It is worth noting that the identifications of markers from non-blood sources provide unique advantages beyond the blood and these alternative sources may be of great significance in offering supplementary information in certain settings. Here, we outline the latest advances in the analysis of non-blood biomarkers, predominantly including urine, saliva, cerebrospinal fluid, pleural fluid, stool and etc. The unique advantages of such testings, their current limitations and the appropriate use of non-blood assays and blood assays in different settings are further discussed. Finally, we propose to highlight the challenges of these alternative assays from basic to clinical implementation and explore the areas where more investigations are warranted to elucidate its potential utility.

For the problem that the abnormal circulation of bipolar double twelve-pulse ultra high voltage direct current (UHVDC) line permanent grounding fault can not be effectively isolated, an optimized scheme for suppressing the abnormal fault circulation is proposed. Firstly, the influencing factors of abnormal circulating current value for DC line permanent grounding fault are analyzed. Secondly, combined with the existing removal strategies of DC line fault in China, the causes of abnormal circulation are analyzed, which are caused by restarting the high-end valve group with communication condition, unsuccessful restart with communication condition or without communication condition after DC line grounding fault happens. Then, a circulating current suppression scheme for DC line permanent ground fault based on pole isolation and blocking after shifting phase 90° strategy is proposed accordingly. Finally, the simulation model is established through real time digital system (RTDS) to verify the effectiveness of the improved scheme. The results show that the scheme proposed in this paper can effectively solve the abnormal circulation problem of DC line permanent grounding fault under different working conditions.

BackgroundHER2-low expression breast cancer (BC) accounts for approximately 45%-55% of all BC cases. The purpose of this study was to investigate the prognostic difference between patients with HER2-low expression and HER2-zero BC.MethodsAn electronic search of Pubmed, Embase, Cochrane Library, and Web of Science databases was performed to screen studies that included prognostic comparisons between HER2-zero and HER2-low expression groups. A total of 14 studies involving 52106 patients were included.ResultsOur results indicated that HER2-low expression was associated with a significant benefit in OS among all patients with early BC (HR, 0.83; 95% CI, 0.78–0.88), patients with hormone-receptor positive BC (HR, 0.83; 95% CI, 0.77–0.89), and patients with TNBC (HR, 0.78; 95% CI, 0.70–0.87). HER2-low expression was associated with a significant benefit in DFS among all patients (HR, 0.81; 95% CI, 0.71–0.93), patients with hormone receptor-positive BC (HR, 0.81; 95% CI, 0.72–0.90), but no significant difference in DFS was found in patients with TNBC (HR, 0.87; 95% CI, 0.65–1.17). HER2-low expression was associated with a significant benefit in RFS among all patients (HR, 0.90; 95% CI, 0.85–0.95), patients with hormone receptor-positive BC (HR, 0.90; 95% CI, 0.84–0.96), but no significant difference in RFS was found in patients with TNBC (HR, 0.80; 95% CI, 0.55–1.16).ConclusionsAmong patients with early-stage BC, patients with HER2-low expression BC had better OS in the overall population, hormone receptor-positive and TNBC subgroups. Besides, favorable DFS and RFS were observed in both the overall population and hormone receptor-positive subgroup.Systematic review registrationhttps://www.crd.york.ac.uk/PROSPERO/, identifier (CRD 42022349458).

In recent years, microfluidic bioreactors have become important in chemical production; however, the production cost is high, and it becomes difficult to balance scale, efficiency, and cost. Therefore, a low-cost, efficient, high-delivery-capacity, green-fluid reactor is urgently required. Herein, a cellulose bioreactor with dual-scale directional channels and a porous inner wall is reported for the continuous catalytic conversion of polydatin into resveratrol. The dual-scale directional channel structure endows the reactor with high mass transfer speed and large transport capacity, resulting in fast fluid diffusion rate and more severe "disturbance" inside the reactor. It accelerates the mass transfer state of the whole reaction and further improves the catalytic performance compared to the uniform channel reactor. The reactor can achieve a high conversion rate of 98.58% of resveratrol within 2 h and exhibits excellent stability, owing to which it has broad application prospects in catalytic reactions, and helps derive a new approach for constructing fluid catalysis bioreactors. [ABSTRACT FROM AUTHOR]

The segmentation of abnormal regions is vital in smart manufacturing. The blurring sauce-packet leakage segmentation task (BSLST) is designed to distinguish the sauce packet and the leakage's foreground and background at the pixel level. However, the existing segmentation system for detecting sauce-packet leakage on intelligent sensors encounters an issue of imaging blurring caused by uneven illumination. This issue adversely affects segmentation performance, thereby hindering the measurements of leakage area and impeding the automated sauce-packet production. To alleviate this issue, we propose the two-stage illumination-aware sauce-packet leakage segmentation (ISLS) method for intelligent sensors. The ISLS comprises two main stages: illumination-aware region enhancement and leakage region segmentation. In the first stage, YOLO-Fastestv2 is employed to capture the Region of Interest (ROI), which reduces redundancy computations. Additionally, we propose image enhancement to relieve the impact of uneven illumination, enhancing the texture details of the ROI. In the second stage, we propose a novel feature extraction network. Specifically, we propose the multi-scale feature fusion module (MFFM) and the Sequential Self-Attention Mechanism (SSAM) to capture discriminative representations of leakage. The multi-level features are fused by the MFFM with a small number of parameters, which capture leakage semantics at different scales. The SSAM realizes the enhancement of valid features and the suppression of invalid features by the adaptive weighting of spatial and channel dimensions. Furthermore, we generate a self-built dataset of sauce packets, including 606 images with various leakage areas. Comprehensive experiments demonstrate that our ISLS method shows better results than several state-of-the-art methods, with additional performance analyses deployed on intelligent sensors to affirm the effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

The growing preference for incorporating microbial aspartic proteases in industries is due to their high catalytic function and high degree of substrate selectivity. These properties, however, are attributable to molecular alterations in their structure and a variety of other characteristics. Molecular tools, functional genomics, and genome editing technologies coupled with other biotechnological approaches have aided in improving the potential of industrially important microbial proteases by addressing some of their major limitations, such as: low catalytic efficiency, low conversion rates, low thermostability, and less enzyme yield. However, the native folding within their full domain is dependent on a surrounding structure which challenges their functionality in substrate conversion, mainly due to their mutual interactions in the context of complex systems. Hence, manipulating their structure and controlling their expression systems could potentially produce enzymes with high selectivity and catalytic functions. The proteins produced by microbial aspartic proteases are industrially capable and far-reaching in regulating certain harmful distinctive industrial processes and the benefits of being eco-friendly. This review provides: an update on current trends and gaps in microbial protease biotechnology, exploring the relevant recombinant strategies and molecular technologies widely used in expression platforms for engineering microbial aspartic proteases, as well as their potential industrial and biotechnological applications. [ABSTRACT FROM AUTHOR]

N6-methyladenosine (m6A), the most prevalent RNA internal modification, is present in most eukaryotic species and prokaryotes. Studies have highlighted an intricate network architecture by which m6A epitranscriptome impacts on immune response and function. However, it was only until recently that the mechanisms underlying the involvement of m6A modification in immune system were uncovered. Here, we systematically review the m6A involvement in the regulation of innate and adaptive immune cells. Further, the interplay between m6A modification and anti-inflammatory, anti-viral and anti-tumour immunity is also comprehensively summarized. Finally, we focus on the future prospects of m6A modification in immune modulation. A better understanding of the crosstalk between m6A modification and immune system is of great significance to reveal new pathogenic pathways and to develop promising therapeutic targets of diseases.

Container technology has become a widely used virtualization technology in cloud platform due to its lightweight virtualization characteristics. However, it shares the kernel with the host, so it has poor security and isolation, and is vulnerable to flood, denial of service, and escape attacks. In order to effectively detect whether the container is attacked or not, an intrusion detection method based on host system call frequency was proposed. This method took advantage of the different frequency of system call between different attack behaviors, collected the system call generated when the container was running, extracted the system call features by combining the sliding window and TF-IDF algorithm, and classified by comparing the feature similarity. The experimental results show that the detection rate of this method can reach 97%, and the false alarm rate is less than 4%.