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Ecological management of the microbiota in patients with cancer
Critical period of weed-crop competition in irrigated chickpea as a tool for judicious weed control
From ASCO 2025
Comparison of segmentation performance of cnns, vision transformers, and hybrid networks for paranasal sinuses with sinusitis on CT images
Abstract Accurate segmentation of the paranasal sinuses, including the frontal sinus (FS), ethmoid sinus (ES), sphenoid sinus (SS), and maxillary sinus (MS), plays an important role in supporting image-guided surgery (IGS) for sinusitis, facilitating safer intraoperative navigation by identifying anatomical variations and delineating surgical landmarks on CT imaging. To the best of our knowledge, no comparative studies of convolutional neural networks (CNNs), vision transformers (ViTs), and hybrid networks for segmenting each paranasal sinus in patients with sinusitis have been conducted. Therefore, the objective of this study was to compare the segmentation performance of CNNs, ViTs, and hybrid networks for individual paranasal sinuses with varying degrees of anatomical complexity and morphological and textural variations caused by sinusitis on CT images. The performance of CNNs, ViTs, and hybrid networks was compared using Jaccard Index (JI), Dice similarity coefficient (DSC), precision (PR), recall (RC), and 95% Hausdorff Distance (HD95) for segmentation accuracy metrics and the number of parameters (Params) and inference time (IT) for computational efficiency. The Swin UNETR hybrid network outperformed the other networks, achieving the highest segmentation scores, with a JI of 0.719, a DSC of 0.830, a PR of 0.935, and a RC of 0.758, and the lowest HD95 value of 10.529 with the smallest number of the model architectural parameter, with 15.705 M Params. Also, CoTr, another hybrid network, demonstrated superior segmentation performance compared to CNNs and ViTs, and achieved the fastest inference time with 0.149 IT. Compared with CNNs and ViTs, hybrid networks significantly reduced false positives and enabled more precise boundary delineation, effectively capturing anatomical relationships among the sinuses and surrounding structures. This resulted in the lowest segmentation errors near critical surgical landmarks. In conclusion, hybrid networks may provide a more balanced trade-off between segmentation accuracy and computational efficiency, with potential applicability in clinical decision support systems for sinusitis.
Zanidatamab shows promise as first-line therapy for advanced-stage HER2+ GEA
Automated drug design for druggable target identification using integrated stacked autoencoder and hierarchically self-adaptive optimization
Study of far-field reduction in high power 940 nm vertical-cavity surface-emitting lasers cascaded by tunnel junctions
Abstract This paper characterizes the performance of 940 nm single-junction (1 J) and triple-junction (3 J) vertical-cavity surface-emitting laser (VCSEL) arrays, tested at room temperature under 1.8 ns pulsed current injection. By suppressing thermal effects, the slope efficiency (SE) of the 1 J VCSEL array reaches 1.05 W/A, while the 3 J VCSEL array achieves 3.2 W/A, with a peak output power exceeding 120 W, demonstrating a significant performance enhancement. Furthermore, we observe that in the 3 J VCSEL array, the far-field (FF) divergence angle gradually decreases with increasing injection current, reducing from approximately 17° to about 5°. The far-field beam profile exhibits a Gaussian distribution, and spectral measurements indicate that the fundamental mode is dominant. We further analyze the characteristics of the VCSEL through both simulations and measurements. Current path analysis reveals that in the 3 J structure, the presence of a highly doped tunnel junction (TJ) and multiple oxide layers alleviates current crowding compared to the 1 J structure, resulting in a different gain distribution. Calculations show that the overlap between the gain region and the fundamental mode is greater than that of higher-order modes, which may explain the dominance of the fundamental mode. The results from single-device testing align with the observations in the VCSEL array, consistently demonstrating fundamental mode dominance. This phenomenon contributes to a reduced divergence angle, presenting a significant advantage for future optoelectronic applications.
Eco-friendly synthesis of silver nanoparticles using Anemone coronaria bulb extract and their potent anticancer and antibacterial activities
Robot-assisted laparoscopic surgery confers improved oncological outcomes
Assessing and predicting crash dynamics with and without road safety measures on the Dejen to Bahir Dar highway in Ethiopia
Preparation of plane trees’ bark biochar/ZnAl-LDH and its adsorption performance for phosphate and recovery
CT imaging findings of corona mortis and a new method for venous typing
Application of hybrid CNN-transformer for classifying major coal mine accident hazards
Analysis of static electricity risks in nonmetallic pipelines for hydrogen transportation
CRFTS: a cluster-centric and reservation-based fault-tolerant scheduling strategy to enhance QoS in cloud computing
Widening socioeconomic inequalities in cancer incidence and related potential to reduce cancer between 2008 and 2019 in Germany
Abstract Background Cancer is one of the main causes of a high burden of disease and one of the strongest contributors to earlier mortality among lower socioeconomic groups in Germany. Therefore, studying socio-economic inequalities in cancer incidence is of high relevance from a public-health and health-equity lens. The aim of this study was to examine in more depth time trends in socioeconomic inequalities in cancer incidence and the related potential for reducing the incidence of specific cancers across Germany. Methods We used epidemiologic data from the Centre for Cancer Registry Data at the Robert Koch Institute and official population statistics for Germany from 2008 to 2019. To analyse trends in socioeconomic inequalities in cancer incidence, we used an ecological study design and linked the cancer registry and population data with the German Index of Socioeconomic Deprivation at district level. We calculated standardised cancer incidence rates for the most common cancers by area-level socioeconomic deprivation and estimated the Slope and Relative Index of Inequality (SII, RII) to determine the extent of area-level socioeconomic inequalities in the risk of cancer. In a what-if analysis, counterfactual scenarios were used to calculate how much lower cancer incidence could be if socioeconomic inequalities in incidence were reduced or eliminated. Results Due to less favourable trends of cancer incidence in more deprived areas, socioeconomic inequalities in cancer incidence has widened to the detriment of residents in highly deprived areas. This was observed for all cancers combined and for several common cancers such as stomach, colorectal and lung cancer among both women and men. In 2017–19, total cancer incidence was 18% (women: RII 1,18) and 49% (men: RII 1,49) higher in the most than in the least deprived area. Reverse inequalities were observed for skin melanoma in both sexes and female breast cancer, the lowest incidence being among residents of highly deprived districts. For 2017–19, the what-if analysis showed that the annual number of newly diagnosed cancers cases would be 9,100–76,000 cases fewer if the socioeconomic gap in cancer incidence between districts could be narrowed or eliminated. Conclusions In Germany, socioeconomic inequalities in cancer incidence have widened in recent decades. Tackling cancer risks in deprived areas could reduce those inequalities and the burden of cancer overall. Our study emphasises the growing importance of structural approaches in cancer prevention for reducing health inequalities in Germany.