A dual-encoder double concatenation Y-shape network for precise volumetric liver and lesion segmentation.

Accurate segmentation of the liver and tumors from CT volumes is crucial for hepatocellular carcinoma diagnosis and pre-operative resection planning. Despite advances in deep learning-based methods for abdominal CT images, fully-automated segmentation remains challenging due to class imbalance and structural variations, often requiring cascaded approaches that incur significant computational costs. In this paper, we present the Dual-Encoder Double Concatenation Network (DEDC-Net) for simultaneous segmentation of the liver and its tumors. DEDC-Net leverages both residual and skip connections to enhance feature reuse and optimize performance in liver and tumor segmentation tasks. Extensive qualitative and quantitative experiments on the LiTS dataset demonstrate that DEDC-Net outperforms existing state-of-the-art liver segmentation methods. An ablation study was conducted to evaluate different encoder backbones - specifically VGG19 and ResNet - and the impact of incorporating an attention mechanism. Our results indicate that DEDC-Net, without any additional attention gates, achieves a superior mean Dice Score (DS) of 0.898 for liver segmentation. Moreover, integrating residual connections into one encoder yielded the highest DS for tumor segmentation tasks. The robustness of our proposed network was further validated on two additional, unseen CT datasets: IDCARDb-01 and COMET. Our model demonstrated superior lesion segmentation capabilities, particularly on IRCADb-01, achieving a DS of 0.629. The code implementation is publicly available at this website.

An insight into recent developments of copper, silver and gold carbon dots: cancer diagnostics and treatment.

Cancer is one of the most fatal diseases globally, however, advancement in the field of nanoscience specifically novel nanomaterials with nano-targeting of cancer cell lines has revolutionized cancer diagnosis and therapy and has thus attracted the attention of researchers of related fields. Carbon Dots (CDs)-C-based nanomaterials-have emerged as highly favorable candidates for simultaneous bioimaging and therapy during cancer nano-theranostics due to their exclusive innate FL and theranostic characteristics exhibited in different preclinical results. Recently, different transition metal-doped CDs have enhanced the effectiveness of CDs manifold in biomedical applications with minimum toxicity. The use of group-11 (Cu, Ag and Au) with CDs in this direction have recently gained the attention of researchers because of their encouraging results. This review summarizes the current developments of group-11 (Cu, Ag and Au) CDs for early diagnosis and therapy of cancer including their nanocomposites, nanohybrids and heterostructures etc. All The manuscript highlights imaging applications (FL, photoacoustic, MRI etc.) and therapeutic applications (phototherapy, photodynamic, multimodal etc.) of Cu-, Ag- and Au-doped CDs reported as nanotheranostic agents for cancer treatment. Sources of CDs and metals alogwith applications to give a comparative analysis have been given in the tabulated form at the end of manuscript. Further, future prospects and challenges have also been discussed.

Edge-exposed MoS2 nanospheres assembled with SnS2 nanosheet to boost NO2 gas sensing at room temperature.

SnS2 nanosheets (NSs) have become an ideal candidate for high performance gas sensors due to their unique sensing properties. However, the restacking and aggregation in the process of sensor manufacturing have great influence on the gas sensing performance. In this study, we synthesized a novel heterojunction of the flower-like porous SnS2 NSs with edge exposed MoS2 nanospheres via a facile hydrothermal method and sensitive response has achieved at room temperature (27℃). After functionalization, the SMS-Ⅱ showed excellent response (Ra/Rg = 25.9-100 ppm NO2), which is 22.3 times higher than that of the pristine SnS2 NSs. The sensor also has the characteristics of short response time of 2 s, excellent base line recovery (28.2 s), long-term stability and reliability within 16 weeks, good selectivity and low detection concentration of only 50 ppb. The p-n heterojunction formed between the edge-exposed spherical MoS2 and the 3D flower-like SnS2 NSs has a synergistic effect, providing a highly active sites for the adsorption of NO2 gas, which greatly enhance the sensitivity of the sensor. Simple fabrication and excellent gas sensing performance of the SnS2/MoS2 heterostructure nanomaterials (NMs) will highly effective for commercial gas sensing application.

One-step synthesis of palladium oxide-functionalized tin dioxide nanotubes: Characterization and high nitrogen dioxide gas sensing performance at room temperature.

Mesoporous palladium oxide (PdO)-functionalized tin dioxide (SnO2) composite nanotubes (SPCTs) were prepared via one-step synthesis by electrospinning technology using ethanol and N,N-dimethylformamide (DMF) as solvents. Compared with pure SnO2 nanotubes, there were abundant mesopores and multiheterojunctions in PdO-functionalized SnO2 nanotubes. The sample with the molar ratio of SnO2:PdO of 100:3 (3-SPCT) exhibited excellent response (∼20.30) as a sensor with fast gas response speed (∼1.33 s) to 100 ppm nitrogen dioxide (NO2) at room temperature (RT), and the detection limit reached to 10 ppb. The improved gas sensing performance of the 3-SPCT sensor was mainly attributed to the synergistic effect: the unique SnO2 tubular structure and well-dispersed mesopores provided the gas diffusion and adsorption channels, oxygen defects and chemisorbed oxygen were taken as the electron trap and charge transfer active sites, and a large number of heterojunctions acted as electron transport channels, thereby increasing the transfer rate.