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Pancreatic cancer is characterized by high malignancy, low early diagnosis rates, and poor prognosis. Approximately 15%-20% of patients at initial diagnosis have resectable pancreatic cancer, 20%-30% have borderline resectable pancreatic cancer, and over 50% are present with unresectable. Surgical resection remains the only potentially curative treatment option available, but the unique anatomical position of the pancreatic head necessitates complex gastrointestinal reconstruction after resection, which may lead to severe complications such as grade B/C pancreatic fistulas and bleeding. Comprehensive preoperative preparation and individualized postoperative management are crucial to reducing perioperative complications, enhancing patient quality of life, and expediting the initiation of adjuvant therapy. This article reviews perioperative integrated management strategies for patients with pancreatic cancer, drawing on literature and our center's experience, including nutritional therapy, psychological support, preoperative jaundice reduction, neoadjuvant treatment, the prevention and management of pancreatic fistulas and postoperative bleeding, with the aim of improving clinical outcomes and overall survival rates.

Inhibitory neurons (INs) consist of distinct subtypes with unique functions. Previous studies on INs mainly focused on single brain regions, and thus it remains unclear whether the modulation of IN subtypes occurs globally across multiple regions. Here, we monitored the activity of different cortical IN subtypes at both macroscale and microscale in mice learning a lever-press task. Learning evoked a global modulation of IN subtypes throughout the cortex. The initial learning phase involved strong activation of vasoactive intestinal peptide-expressing INs (VIP-INs) and weak activation of somatostatin-expressing INs (SOM-INs). Inactivating VIP-INs increased SOM-IN activity and impaired initial learning. Concurrently, cortical cholinergic inputs from the basal forebrain were initially more active but became less engaged over learning. Manipulation of the cholinergic system impaired motor learning and differentially altered activity of IN subtypes. These results reveal that motor learning involves a global and subtype-specific modulation on cortical INs regulated by the cholinergic system.

Metabolic reprogramming provides tumors with an energy source and biofuel to support their survival in the malignant microenvironment. Extensive research into the intrinsic oncogenic mechanisms of the tumor microenvironment (TME) has established that cancer-associated fibroblast (CAFs) and metabolic reprogramming regulates tumor progression through numerous biological activities, including tumor immunosuppression, chronic inflammation, and ecological niche remodeling. Specifically, immunosuppressive TME formation is promoted and mediators released via CAFs and multiple immune cells that collectively support chronic inflammation, thereby inducing pre-metastatic ecological niche formation, and ultimately driving a vicious cycle of tumor proliferation and metastasis. This review comprehensively explores the process of CAFs and metabolic regulation of the dynamic evolution of tumor-adapted TME, with particular focus on the mechanisms by which CAFs promote the formation of an immunosuppressive microenvironment and support metastasis. Existing findings confirm that multiple components of the TME act cooperatively to accelerate the progression of tumor events. The potential applications and challenges of targeted therapies based on CAFs in the clinical setting are further discussed in the context of advancing research related to CAFs. [ABSTRACT FROM AUTHOR]

Various amounts of TiSi2 (30, 40, and 50 wt.%) were added to 3 mol% yttria stabilized tetragonal zirconia polycrystals (3Y‐TZP) to fabricate 3Y‐TZP/TiSi2 composites by vacuum sintering. The effects of the TiSi2 added amount, as well as the sintering temperature on the microstructure, mechanical, and electrical characteristics of the 3Y‐TZP/TiSi2 composites were examined. The sintered samples consisted of three phases: tetragonal (t‐ZrO2), TiSi2, and reaction product Ti5Si3. The maximum bending strength and relative density of the composites, reaching 501.20 MPa and 98.59% respectively, were achieved at a TiSi2 content of 30 wt.% and sintering temperature of 1500°C. The resistivity of 3Y‐TZP/TiSi2 composites showed a nonlinear decrease with increasing TiSi2 content. These results indicated that 3Y‐TZP/TiSi2 composites had a typical percolation threshold phenomenon due to the different TiSi2 content and a conductivity model of 3Y‐TZP/TiSi2 composites at room temperature was founded on the generalized effective medium equation. The resistivity of the composites could optionally adjust between 102 and 10−4Ω·cm with 30–50 wt.% TiSi2 under room temperature. Overall, the 3Y‐TZP/TiSi2 composites show great potential for applications in the heat‐not‐burn tobacco field. [ABSTRACT FROM AUTHOR]

蔗糖脂肪酸酯简称蔗糖酯，是一种良好的表面活性剂，被普遍应用于食品工业。蔗糖酯的合成方法主要包括化学法和酶法，对蔗糖酯的化学合成法进行了详细介绍，概述了酰氯酯化法及酯交换法的操作步骤、优选工艺及优缺点，并与酶法进行了对比。概述了蔗糖酯的结构、理化性质、应用及工业发展现状，以期为蔗糖酯的工业化生产提供参考。 Sucrose fatty acid ester, sucrose ester for short, is a good surfactant and is widely used in food industry. The synthesis methods of sucrose ester are mainly divided into chemical method and enzymatic method. The chemical synthesis method of sucrose ester was introduced in detail, and the operation steps, preferred processes, advantages and disadvantages of acyl chloride esterification method and transesterification method were summarized, and it was compared with enzymatic method. The structure, physicochemical properties, application and industrial development status of sucrose ester were briefly described, in order to provide reference for the industrial production of sucrose ester.

Femtosecond laser processing technology has been used to achieve controlled processing of microtips array on the surface of polycrystalline LaB6 blocks. Under the condition of ensuring the integrity of the geometric morphology of the tips array, the tips with a height of 10 μm and a radius of curvature of 1 μm can be processed. The distribution of tips in the array is uniform, the morphology is complete, the crystal structure and physical phase of LaB6 have not changed after processing, which breaks through the technical problems of difficult processing and poor geometry consistency about polycrystalline rare-earth hexaboride tips emitter, and the processing area is no longer limited by the small size of single crystals. The field emission performance test indicated that the turn-on electric field is 2.8 V/μm, and the current density is 467.9 mA/cm2 when the applied electric field reached 9.4 V/μm. [ABSTRACT FROM AUTHOR]

Retinal vessel segmentation plays a vital role in the medical field, facilitating the identification of numerous chronic conditions based on retinal vessel images. These conditions include diabetic retinopathy, hypertensive retinopathy, glaucoma, and others. Although the U-Net model has shown promising results in retinal vessel segmentation, it tends to struggle with fine branching and dense vessel segmentation. To further enhance the precision of retinal vessel segmentation, we propose a novel approach called transformer dilated convolution attention U-Net (TDCAU-Net), which builds upon the U-Net architecture with improved Transformer-based dilated convolution attention mechanisms. The proposed model retains the three-layer architecture of the U-Net network. The Transformer component enables the learning of contextual information for each pixel in the image, while the dilated convolution attention prevents information loss. The algorithm efficiently addresses several challenges to optimize blood vessel detection. The process starts with five-step preprocessing of the images, followed by chunking them into segments. Subsequently, the retinal images are fed into the modified U-Net network introduced in this paper for segmentation. The study employs eye fundus images from the DRIVE and CHASEDB1 databases for both training and testing purposes. Evaluation metrics are utilized to compare the algorithm's results with state-of-the-art methods. The experimental analysis on both databases demonstrates that the algorithm achieves high values of sensitivity, specificity, accuracy, and AUC. Specifically, for the first database, the achieved values are 0.8187, 0.9756, 0.9556, and 0.9795, respectively. For the second database, the corresponding values are 0.8243, 0.9836, 0.9738, and 0.9878, respectively. These results demonstrate that the proposed approach outperforms state-of-the-art methods, achieving higher performance on both datasets. The TDCAU-Net model presented in this study exhibits substantial capabilities in accurately segmenting fine branching and dense vessels. The segmentation performance of the network surpasses that of the U-Net algorithm and several mainstream methods. [ABSTRACT FROM AUTHOR]