Sulforaphane Mediates Glutathione Depletion via Polymeric Nanoparticles to Restore Cisplatin Chemosensitivity

Platinum (Pt)-based chemotherapy is a widely used therapeutic regimen against various cancers. However, the insufficient cellular uptake, deactivation by thiol-containing species and nonspecific distribution of cisplatin (CDDP) result in its low chemosensitivity as well as systemic side effects, which can largely constrain the employment of CDDP in clinical treatment. To circumvent these problems, in this study, polymeric nanoparticles were utilized to co-deliver a water-soluble CDDP derivative, poly (γ, L-glutamic acid)-CDDP conjugate, and a naturally occurring compound derived from broccoli, sulforaphane, which can achieve efficient glutathione (GSH) depletion, to enhance the accumulation of CDDP in cancer cells. Results show that compared with combinational treatment of CDDP and SFN, the nanoparticles were more effectively internalized and could significantly reduce GSH content in breast cancer cells, leading to a notable increase in DNA-bound Pt and DNA damage-induced apoptosis. Moreover, in an orthotopic breast cancer model, the nanoparticles achieved a significantly higher tumor accumulation and exhibited a more powerful anti-tumor activity. Finally, this nano-enhanced chemotherapy was further confirmed in a liver cancer model with high-expression of GSH. Taken together, this sulforaphane-based nano-strategy holds great promise to enhance the sensitivity and therapeutic efficacy of Pt-based chemotherapy

Hyper-IL-15 suppresses metastatic and autochthonous liver cancer by promoting tumour-specific CD8+ T cell responses

Liver cancer has a very dismal prognosis due to lack of effective therapy. Here, we studied the therapeutic effects of hyper-interleukin15 (hyper-IL-15), which is composed of IL-15 and the sushi domain of the IL-15 receptor α chain, on metastatic and autochthonous liver cancers

A Novel Semi-Supervised Dynamic Classifier Selection Method for HSI Classification Based on SP Segmentation

This paper proposes a novel hyperspectral image classification method that combines dynamic semi-supervised multiple-kernel collaborative representation ensemble selection with superpixel (SP) consistency constraints. The method is based on the consistency principle of labels within SP blocks, where the hyperspectral image is divided into different SP blocks, and each block is treated as an independent classification task. It applies a dynamic ensemble selection strategy to select high-confidence samples from the unlabeled data and assigns pseudo-labels to expand the available training sample set. Additionally, it employs a multiple-kernel collaborative representation classifier as the base classifier to better capture sample similarities and correlations, thereby improving the classification performance. Experimental results demonstrate that the proposed method achieves superior classification accuracy on various datasets such as Indian Pines, Purdue, and KSC, outperforming the traditional Meta-DES method significantly

Goos-hänchen-like shift of three-level matter wave incident on Raman beams

When a three-level atomic wavepacket is obliquely incident on a "medium slab" consisting of two far-detuned laser beams, there exists lateral shift between reflection and incident points at the surface of a "medium slab", analogous to optical Goos-Hänchen effect. We evaluate lateral shifts for reflected and transmitted waves via expansion of reflection and transmission coefficients, in contrast to the stationary phase method. Results show that lateral shifts can be either positive or negative dependent on the incident angle and the atomic internal state. Interestingly, a giant lateral shift of transmitted wave with high transmission probability is observed, which is helpful to observe such lateral shifts experimentally. Different from the two-level atomic wave case, we find that quantum interference between different atomic states plays crucial role on the transmission intensity and corresponding lateral shifts

Recognition of FT-IR Data Cuscutae Semen, Japanese Dodder, and Sinapis Semen Using Discrete Wavelet Transformation and RBF Networks

Horizontal attenuation total reflection Fourier transformation infrared spectroscopy (HATR-FT-IR) studies on cuscutae semen and its confusable varieties Japanese dodder and sinapis semen combined with discrete wavelet transformation (DWT) and radial basis function (RBF) neural networks have been conducted in order to classify them. DWT is used to decompose the FT-IRs of cuscutae semen, Japanese dodder, and sinapis semen. Two main scales are selected as the feature extracting space in the DWT domain. According to the distribution of cuscutae semen, Japanese dodder, and sinapis semen’s FT-IRs, three feature regions are determined at detail 3, and two feature regions are determined at detail 4 by selecting two scales in the DWT domain. Thus five feature parameters form the feature vector. The feature vector is input to the RBF neural networks to train so as to accurately classify the cuscutae semen, Japanese dodder, and sinapis semen. 120 sets of FT-IR data are used to train and test the proposed method, where 60 sets of data are used to train samples, and another 60 sets of FT-IR data are used to test samples. Experimental results show that the accurate recognition rate of cuscutae semen, Japanese dodder, and sinapis semen is average of 100.00%, 98.33%, and 100.00%, respectively, following the proposed method

Carbon Sink Cost and Influence Factors Analysis in a National Afforestation Project under Different Investment Modes

Afforestation projects are the main source of carbon sink. Measurement and impact analysis of carbon sink costs will help accelerate the marketization of forestry carbon sink. Considering the opportunity cost of land use and the carbon release cost of wood products, this study proposed a forestry carbon sink cost model under the Public–Private Partnership (PPP) and the direct (DI) investment mode based on the classic carbon sink model. Then, the proposed models were applied to a real-world afforestation project, the 20-year national afforestation project (NAP) in Laohekou City, Hubei Province, China. With the help of the input–output forestry carbon sink cost–benefit analysis framework, the dynamic analysis of factors such as rotation period, timber price, discount rate and yield rate for forestry is carried out. Results show that: (1) with the increasing of rotation period, wood market price, and wood yield rate, the carbon sink cost of Laohekou NAP gradually decreases, while the discount rate has the opposite trend; (2) the DI mode is more feasible than the PPP model at the present condition. The PPP mode is more feasible than the DI mode only when the wood price is lower than 73.18% of the current price, the yield rate is lower than 0.485, and the discount rate is higher than 6.77%. (3) When choosing tree species for NAP, the carbon sink capacity, wood market price, maturity time, and planting cost should be synthetically considered. The proposed model and the obtained results can not only support local governments and forestry carbon sink enterprises to make tradeoffs between PPP and DI mode, but also provide them with useful information for reducing carbon sink costs

High-efficient extraction of principal medicinal components from fresh Phellodendron bark (cortex phellodendri)

There are three key medicinal components (phellodendrine, berberine and palmatine) in the extracts of Phellodendron bark, as one of the fundamental herbs of traditional Chinese medicine. Different extraction methods and solvent combinations were investigated to obtain the optimal technologies for high-efficient extraction of these medicinal components. Results: The results showed that combined solvents have higher extracting effect of phellodendrine, berberine and palmatine than single solvent, and the effect of ultrasonic extraction is distinctly better than those of distillation and soxhlet extraction. Conclusion: The hydrochloric acid/methanol-ultrasonic extraction has the best effect for three medicinal components of fresh Phellodendron bark, providing an extraction yield of 103.12 mg/g berberine, 24.41 mg/g phellodendrine, 1.25 mg/g palmatine. Keywords: Phellodendron, Cortex phellodendri, Extraction methods, Medicinal component