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Being rich in anthocyanin is one of the most important physiological traits of mulberry fruits. Efficient and non-destructive detection of anthocyanin content and distribution in fruits is important for the breeding, cultivation, harvesting and selling of them. This study aims at building a fast, non-destructive, and high-precision method for detecting and visualizing anthocyanin content of mulberry fruit by using hyperspectral imaging. Visible near-infrared hyperspectral images of the fruits of two varieties at three maturity stages are collected. Successive projections algorithm (SPA), competitive adaptive reweighted sampling (CARS) and stacked auto-encoder (SAE) are used to reduce the dimension of high-dimensional hyperspectral data. The least squares-support vector machine and extreme learning machine (ELM) are used to build models for predicting the anthocyanin content of mulberry fruit. And genetic algorithm (GA) is used to optimize the major parameters of models. The results show that the higher the anthocyanin content is, the lower the spectral reflectance is. 15, 7 and 13 characteristic variables are extracted by applying CARS, SPA and SAE respectively. The model based on SAE-GA-ELM achieved the best performance with R 2 of 0.97 and the RMSE of 0.22 mg/g in both the training set and testing set, and it is applied to retrieve the distribution of anthocyanin content in mulberry fruits. By applying SAE-GA-ELM model to each pixel of the mulberry fruit images, distribution maps are created to visualize the changes in anthocyanin content of mulberry fruits at three maturity stages. The overall results indicate that hyperspectral imaging, in combination with SAE-GA-ELM, can help achieve rapid, non-destructive and high-precision detection and visualization of anthocyanin content in mulberry fruits.

Background Triple negative breast cancer (TNBC) is an aggressive breast cancer subtype characterized with poor prognosis and high metastatic potential. Although traditional chemotherapy, radiation, and surgical resection remain the standard treatment options for TNBC, bispecific antibody-based immunotherapy is emerging as new strategy in TNBC treatment. Here, we found that the receptor tyrosine kinase-like Orphan Receptor 1 (ROR1) was highly expressed in TNBC but minimally expressed in normal tissue. A bispecific ROR1-targeted CD3 T cell engager (TCE) was designed in IgG-based format with extended half-life. Method The expression of ROR1 in TNBC was detected by RT-qPCR and immunohistology analysis. The killing of ROR1/CD3 antibody on TNBC cells was determined by the in vitro cytotoxicity assay and in vivo PBMC reconstituted mouse model. The activation of ROR1/CD3 on T cells was analyzed by the flow cytometry and ELISA assay. Pharmacokinetics study of ROR1/CD3 was performed in mouse. Results The ROR1/CD3 TCE triggered T cell activation and proliferation, which showed potent and specific killing to TNBC cells in ROR1-depedent manner. In vivo mouse model indicated that ROR1/CD3 TCE redirected the cytotoxic activity of T cells to lyse TNBC cells and induced significant tumor regression. Additionally, the ROR1/CD3 bispecific antibody exhibited an extended half-life in mouse, which may enable intermittent administration in clinic. Conclusions Collectively, these results demonstrated that ROR1/CD3 TCE has a promising efficacy profile in preclinical studies, which suggested it as a possible option for the treatment of ROR1-expressing TNBC.

Hyperspectral imaging (HSI) technology has great potential for the efficient and accurate detection of plant diseases. To date, no studies have reported the identification of yellow vein clearing disease (YVCD) in lemon plants by using hyperspectral imaging. A major challenge in leveraging HSI for rapid disease diagnosis lies in efficiently processing high-dimensional data without compromising classification accuracy. In this study, hyperspectral feature extraction is optimized by introducing a novel hybrid 3D-2D-LcNet architecture combined with three-dimensional (3D) and two-dimensional (2D) convolutional layers—a methodological advancement over conventional single-mode CNNs. The competitive adaptive reweighted sampling (CARS) and successive projection algorithm (SPA) were utilized to reduce the dimensionality of hyperspectral images and select the feature wavelengths for YVCD diagnosis. The spectra and hyperspectral images retrieved through feature wavelength selection were separately employed for the modeling process by using machine learning algorithms and convolutional neural network algorithms (CNN). Machine learning algorithms (such as support vector machine and partial least squares discriminant analysis) and convolutional neural network algorithms (CNN) (including 3D-ShuffleNetV2, 2D-LcNet and 2D-ShuffleNetV2) were utilized for comparison analysis. The results showed that CNN-based models have achieved an accuracy ranging from 93.90% to 97.35%, significantly outperforming machine learning approaches (ranging from 68.83% to 93.52%). Notably, the hybrid 3D-2D-LcNet has achieved the highest accuracy of 97.35% (CARS) and 96.86% (SPA), while reducing computational costs compared to 3D-CNNs. These findings suggest that hybrid 3D-2D-LcNet effectively balances computational complexity with feature extraction efficacy and robustness when handling spectral data of different wavelengths. Overall, this study offers insights into the rapidly processing hyperspectral images, thus presenting a promising method.

Circulating miRNAs (cirmiRNAs) can be packaged into the exosomes, participating in intercellular communication, which affects the malignant progression and therapy resistance of triple‐negative breast cancer (TNBC). Currently, immune checkpoint inhibitors that regulate T‐cell function, especially antibodies against programmed cell death 1 (PD‐1) or its ligand PD‐L1, are emerging as new promising therapy for TNBC patients. However, only very limited patients showed complete or partial response to anti‐PD‐1 treatment. Dysfunction of CD8+ T cells is one of the key reasons for the immune escape of TNBC. The regulation of exosome‐derived cirmiRNAs on CD8+ T cells in TNBC deserves more investigation. Here, the cirmiR‐20a‐5p level was significantly upregulated in the plasma of TNBC patients and culture supernatant of TNBC cells. High abundance of cirmiR‐20a‐5p was correlated with a worse prognosis of TNBC. cirmiR‐20a‐5p was secreted in the form of exosomes by TNBC cells. Exosomal cirmiR‐20a‐5p was internalized into CD8+ T cells and resulted into the dysfunction of CD8+ T. A mechanism study uncovered that cirmiR‐20a‐5p targeted the nuclear protein ataxia‐telangiectasia (NPAT) and decreased NPAT expression in CD8+ T cells. An in vivo xenograft mouse model showed that cirmiR‐20a‐5p conferred TNBC to anti‐PD‐1 treatment resistance. Collectively, these findings indicated that cirmiR‐20a‐5p released by TNBC cells via exosome promotes cancer cell growth and leads to the immunosuppression by inducing CD8+ T cell dysfunction. This study suggests that targeting cirmiR‐20a‐5p might be a novel strategy for overcoming the resistance of TNBC to anti‐PD‐1 immunotherapy. Exosomal cirmiR‐20a‐5p was upregulated in triple‐negative breast cancer (TNBC) and correlated with the poor prognosis of TNBC patients. cirmiR‐20a‐5p released via exosomes by TNBC cells was uptaken by CD8+ T cells and led to the dysfunction of CD8+ T cells by targeting nuclear protein ataxia‐telangiectasia. Increased cirmiR‐20a‐5p enhanced the resistance of TNBC to anti‐PD‐1 therapy. These results suggest that targeting cirmiR‐20a‐5p may be a novel strategy for improving the immunotherapy efficacy of TNBC patients.

Protein content is one of the most important indicators for assessing the quality of mulberry leaves. This work is carried out for the rapid and non-destructive detection of protein content of mulberry leaves using hyperspectral imaging (HSI) (Specim FX10 and FX17, Spectral Imaging Ltd., Oulu, Finland). The spectral range of the HSI acquisition system and data processing methods (pretreatment, feature extraction, and modeling) is compared. Hyperspectral images of three spectral ranges in 400–1,000 nm (Spectral Range I), 900–1,700 nm (Spectral Range II), and 400–1,700 nm (Spectral Range III) were considered. With standard normal variate (SNV), Savitzky–Golay first-order derivation, and multiplicative scatter correction used to preprocess the spectral data, and successive projections algorithm (SPA), competitive adaptive reweighted sampling, and random frog used to extract the characteristic wavelengths, regression models are constructed by using partial least square and least squares-support vector machine (LS-SVM). The protein content distribution of mulberry leaves is visualized based on the best model. The results show that the best results are obtained with the application of the model constructed by combining SNV with SPA and LS-SVM, showing an R 2 of up to 0.93, an RMSE of just 0.71 g/100 g, and an RPD of up to 3.83 based on the HSI acquisition system of 900–1700 nm. The protein content distribution map of mulberry leaves shows that the protein of healthy mulberry leaves distributes evenly among the mesophyll, with less protein content in the vein of the leaves. The above results show that rapid, non-destructive, and high-precision detection of protein content of mulberry leaves can be achieved by applying the SWIR HSI acquisition system combined with the SNV-SPA-LS-SVM algorithm.

Metal particles and surface charge accumulation are considered the key factors that could trigger unexpected flashovers of insulators equipped in gas-insulated switchgear (GIS). In eco-friendly gases, the flashover properties and the synergistic effect of the surface charge and the metal particle on flashover remain unclear. This study investigates the flashover properties of down-scaled 252 kV GIS basin-type epoxy insulators with metal particles in C4F7N/CO2 mixtures, with and without AC pre-charging. Tests considered various particle adherence locations and a particle-free control group. The results indicated that metal particles at the high-voltage (HV) electrode or middle area reduce flashover voltage, with the HV electrode and concave surface being most critical. Surface charges, induced by pre-charging and metal particle attachment, interact synergistically with the metal particle during the flashover process, increasing the flashover voltage and redirecting arcs away from them. Such findings enhance understanding of flashover mechanisms in eco-friendly gas-insulated systems and inform insulator design.

Background Triple negative breast cancer (TNBC) continues to be the most aggressive subtype of breast cancer that frequently develops resistance to chemotherapy. Doxorubicin (DOX) belongs to the anthracycline chemical class of the drug and is one of the widely used anticancer drugs. This study investigates the mechanism of m6A methyltransferase ZC3H13 in DOX resistance of TNBC. Methods ZC3H13, KCNQ1OT1, and TRABD expressions in TNBC tissues or cells were detected by RT-qPCR or Western blot. The effect of ZC3H13 on DOX resistance of TNBC cells was evaluated by CCK-8, clone formation, and EdU staining. RIP was performed to analyze the enrichment of YTHDF2 or m6A on KCNQ1OT1. RIP and RNA pull-down verified the binding between KCNQ1OT1 and MLL4. The enrichment of MLL or H3K9me1/2/3 on TRABD promoter was analyzed by ChIP. A nude mouse xenograft tumor model was established to verify the mechanism in vivo. Results ZC3H13 was poorly expressed in TNBC, and its expression further decreased in drug-resistant cells. Overexpression of ZC3H13 decreased the IC50 of drug-resistant TNBC cells to DOX, repressed proliferation, and induced ferroptosis. Mechanistically, ZC3H13-mediated m6A modification reduced the transcriptional stability of KCNQ1OT1 and inhibited its expression in a YTHDF2-dependent manner. KCNQ1OT1 enhanced the enrichment of H3K4me1/2/3 on TRABD promoter by recruiting MLL4, thus increasing TRABD expression. ZC3H13 induced ferroptosis by inhibiting KCNQ1OT1/TRABD, thereby restraining the growth of DOX-treated tumors in vivo. Conclusion ZC3H13-mediated m6A modification reduces DOX resistance in TNBC by promoting ferroptosis via KCNQ1OT1/TRABD axis. Graphical Abstract

Background: Since lobaplatin (LBP) has been approved to treat metastatic breast cancer in China, this study aimed to evaluate the safety and efficacy of LBP-based chemotherapy in clinical practice. Methods: This trial was a prospective, open-label, multicenter phase IV clinical trial that enrolled patients with unresectable locally advanced or recurrent/metastatic breast cancer from 34 sites between July 2013 and March 2017. Patients were treated with LBP monotherapy or in combination for four to six cycles. The primary endpoint was safety. Secondary endpoints included progression-free survival (PFS), objective response rate (ORR), and disease control rate (DCR). Results: A total of 1179 patients were analyzed; 59 (5.0%) were treated with LBP alone, 134 (11.4%) with LBP plus paclitaxel, 263 (22.3%) with LBP plus docetaxel, 237 (20.1%) with LBP plus gemcitabine, 403 (34.2%) with LBP plus vinorelbine, and 83 (7.0%) with other LBP-based regimens. The overall incidence of adverse events (AEs) was 95.2%, and 57.9% of patients had grade >3 AEs. The most common grade >3 AEs were neutropenia (43.9%), leukopenia (39.4%), anemia (17.8%), and thrombopenia (17.7%). LBP monotherapy showed the lowest incidence of grade >3 AEs (39.0%), followed by LBP plus docetaxel (52.9%), LBP plus paclitaxel (59.0%), LBP plus vinorelbine (62.5%), and LBP plus gemcitabine (62.9%). The ORR and DCR were 36.8 and 77.0%, respectively. The median PFS was 5.5 months (95% confidence interval: 5.2–5.9). Conclusion: LBP-based chemotherapy shows favorable efficacy in patients with advanced breast cancer, with manageable safety profile. Trial registration: This trial was registered with ChiCTR.org.cn, ChiCTR-ONC-13003471.

In this research, experimental research and finite element modelling of glulam-concrete composite (GCC) beams were undertaken to study the flexural properties of composite beams containing timber board interlayers. The experimental results demonstrated that the failure mechanism of the GCC beam was the combination of bend and tensile failure of the glulam beam. The three-dimensional non linear finite element model was confirmed by comparing the load-deflection curve and load-interface slip curve with the experimental results. Parametric analyses were completed to explore the impacts of the glulam beam height, shear connector spacing, timber board interlayer thickness and concrete slab thickness on the flexural properties of composite beams. The numerical outcomes revealed that with an increase of glulam beam height, the bending bearing capacity and flexural stiffness of the composite beams were significantly improved. The timber boards were placed on top of the glulam members and used as the formwork for concrete slab casting. In addition, the flexural properties of composite beams were improved with the increase of the timber board thickness. With the elevation of the shear connector spacing, the ultimate bearing capacity and bending stiffness of composite beams were decreased. The bending bearing capacity and flexural rigidity of the GCC beams were ameliorated with the increase of concrete slab thickness.

To explore the microbial community structure and ecological function of mulberry and their potential relationship with the resistance of mulberry, the community structure and function of endophytic fungi in 18 mulberry cultivars were analyzed and predicted by using high-throughput sequencing technology and the FUNGuild database. A total of 352 operational taxonomic units of fungi were observed at a 97% similarity level, representing six phyla of fungi, Fungi_unclassified, Ascomycota, Basidiomycota, Zygomycota, Rozellomycota, and Chytridiomycota. Fungi_unclassified was dominant, and Ascomycota was relatively dominant in all cultivars. At the genus level, Ascomycota_unclassified was dominant, and Ampelomyces was relatively dominant, with a richness in TAIWANCHANGGUOSANG 16.47–8975.69 times that in the other cultivars. Classified Ascomycota_unclassified was 4.75–296.65 times more common in NANYUANSIJI than in the other cultivars. Based on the FUNGuild analysis method, we successfully annotated six nutrient types, namely, pathotroph, pathotroph–saprotroph, pathotroph–saprotroph–symbiotroph, saprotroph, saprotroph–symbiotroph, and symbiotroph, among which saprophytic–symbiotic accounted for the largest proportion and was absolutely dominant in TWC. This research suggests that community composition differs among cultivars and that the diversity and richness of endophytic fungi in resistant cultivars are higher than those in susceptible cultivars. The ecological functions of cultivars with different resistances are quite different.