Calreticulin couples with immune checkpoints in pancreatic cancer

Clinical and Translational Medicine, Год журнала: 2020, Номер 10(1), С. 36 - 44

Опубликована: Март 1, 2020

Abstract Although immune checkpoint blockade is considered to be the dominant approach in future cancer immunotherapy, whether it will apply pancreatic remains largely unknown. To address this issue, cancer–associated datasets were individually collected by Gene Expression Profiling Interactive Analysis 2 (GEPIA2), cBioPortal, and Tumor Immune System Interaction Database (TISIDB), subsequently subjected prognostic, genomic, immunologic analyses of all well‐established checkpoints. The results indicate that checkpoints might not ideal targets for therapy. Intriguingly, genomic alteration calreticulin, key mediator chemotherapy‐induced immunogenic cell death, was found couple with cancer. Moreover, calreticulin observed highly expressed adenocarcinoma, high expression significantly favors both overall survival disease‐free patients adenocarcinoma. Importantly, further revealed closely related anti‐tumor immunity including multiple effector molecules T‐cell signatures. Taken together, calreticulin‐based therapy may represent a more promising prospect immunotherapy than

Язык: Английский

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Deep learning for automatic tumor lesions delineation and prognostic assessment in multi-modality PET/CT: A prospective survey

Engineering Applications of Artificial Intelligence, Год журнала: 2023, Номер 123, С. 106276 - 106276

Опубликована: Апрель 28, 2023

Язык: Английский

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Gut microbiota patterns associated with somatostatin in patients undergoing pancreaticoduodenectomy: a prospective study

Cell Death Discovery, Год журнала: 2020, Номер 6(1)

Опубликована: Сен. 28, 2020

Postoperative pancreatic fistula (POPF) is a common and dreaded complication after pancreaticoduodenectomy (PD). The gut microbiota has been considered as an crucial mediator of postoperative complications, however, the precise roles in POPF are unclear. A prospective study was developed to explore effects somatostatin on we aim identify microbial alterations process POPF. total 45 patients were randomly divided into PD group or additional therapy group. fecal sample each patient collected preoperatively postoperatively analyzed by 16S rRNA sequencing. Our found that independent risk factor for occurrence POPF, it reduced diversity richness patients. At genus level, led decreased abundance Bifidobacterium, Subdoligranulum Dubosiella, whereas Akkermansia, Enterococcus Enterobacter increased. levels certain bacteria have significantly shifted with LEfSe analysis revealed Ruminococcaceae could be used markers distinguishing high Furthermore, Verrucomicrobia Akkermansia preoperative biomarkers identifying without highlights specific communities related discovers POPF-associated marker, which suggests may become diagnostic biomarker potential therapeutic target

Язык: Английский

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G2NPAN: GAN-guided nuance perceptual attention network for multimodal medical fusion image quality assessment

Frontiers in Neuroscience, Год журнала: 2024, Номер 18

Опубликована: Май 13, 2024

Multimodal medical fusion images (MMFI) are formed by fusing of two or more modalities with the aim displaying as much valuable information possible in a single image. However, due to different strategies various algorithms, quality generated fused is uneven. Thus, an effective blind image assessment (BIQA) method urgently required. The challenge MMFI enable network perceive nuances between qualities, and key point for success BIQA availability valid reference information. To this end, work proposes generative adversarial (GAN) -guided nuance perceptual attention (G2NPAN) implement MMFI. Specifically, we achieve evaluation style via design GAN develop Unique Feature Warehouse module learn features from pixel level. redesigned loss function guides quality. In class activation mapping supervised employed obtain score. Extensive experiments validation have been conducted database images, proposed superior state-of-the-art method.

Язык: Английский

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A Systematic Review of Real-Time Deep Learning Methods for Image-Based Cancer Diagnostics

Journal of Multidisciplinary Healthcare, Год журнала: 2024, Номер Volume 17, С. 4411 - 4425

Опубликована: Сен. 1, 2024

Deep Learning (DL) drives academics to create models for cancer diagnosis using medical image processing because of its innate ability recognize difficult-to-detect patterns in complex, noisy, and massive data. The use deep learning algorithms real-time is explored depth this work. Real-time determines the illness or condition that accounts a patient's symptoms outward physical manifestations within predetermined time frame. With waiting period anywhere between 5 days 30 days, there are currently several ways, including screening tests, biopsies, other prospective methods, can assist discovering problem, particularly cancer. This article conducts thorough literature review understand how DL affects length period. In addition, accuracy turnaround different imaging modalities evaluated with DL-based diagnosis. Convolutional neural networks critical diagnosis, achieving up 99.3% accuracy. effectiveness cost infrastructure required image-based diagnostics evaluated. According report, generalization problems, data variability, explainable some most significant barriers clinical trials. Making applicable will be made possible by DL.

Язык: Английский

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Novel fluorescent GLUT1 inhibitor for precision detection and fluorescence image‐guided surgery in oral squamous cell carcinoma

International Journal of Cancer, Год журнала: 2022, Номер 151(3), С. 450 - 462

Опубликована: Апрель 28, 2022

Abstract Early detection and complete resection of oral squamous cell carcinoma (OSCC) are crucial to improving patient survival prognosis. However, specifically targeted imaging probes for OSCC limited. Our study aimed synthesize a novel near‐infrared fluorescence (NIRF) probe precision image‐guided surgery in OSCC. Bioinformatics data indicated that glucose transporter 1 (GLUT1) is highly expressed patients with We demonstrated high specific GLUT1 expression upon immunohistochemical staining samples from 20 The was further validated both human lines tumor xenografts. Based on these findings, the inhibitor WZB117 utilized NIRF probe, WZB117‐IR820. molecular revealed WZB117‐IR820 could bind areas an orthotopic mouse model after intravenous injection be applied no residual CAL27‐fLUC model. For clinical translational application OSCC, precise delineation achieved topical by histopathological analyses. In conclusion, we synthesized fluorescent WZB117‐IR820, which has potential applications early observable toxicity.

Язык: Английский

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A review on multimodal medical image fusion towards future research

Multimedia Tools and Applications, Год журнала: 2022, Номер 82(5), С. 7361 - 7382

Опубликована: Авг. 20, 2022

Язык: Английский

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Development and Validation of a Nomogram Based on Perioperative Factors to Predict Post-hepatectomy Liver Failure

Journal of Clinical and Translational Hepatology, Год журнала: 2021, Номер 000(000), С. 000 - 000

Опубликована: Март 15, 2021

Background and AimsPost-hepatectomy liver failure (PHLF) is a severe complication main cause of death in patients undergoing hepatectomy. The aim this study was to build predictive model PHLF

Язык: Английский

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A review on treatments of hepatocellular carcinoma—role of radio wave ablation and possible improvements

Egyptian Liver Journal, Год журнала: 2022, Номер 12(1)

Опубликована: Апрель 27, 2022

Abstract Background Currently, several treatment options are available for liver cancer depending on various factors such as location, size, shape, and function. Image fusion is required the diagnosis, intervention, follow-up of certain HCCs. Presently, mental only way while diagnosing lesions by comparing ultrasound (US) image with computed tomography (CT) image. Nevertheless, bound to have errors. The objective this paper study present hepatocellular carcinoma review options, list out their potential limitations, a possible alternative solution based findings reduce errors mistargeting. Methods This systematic carcinoma, especially radio wave ablation. Results It found that computer registration. Conclusions Although best use ablation, there been few open-ended questions further explore.

Язык: Английский

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Advanced AI-driven image fusion techniques in lung cancer diagnostics: systematic review and meta-analysis for precisionmedicine

Robotic Intelligence and Automation, Год журнала: 2024, Номер 44(4), С. 579 - 593

Опубликована: Июнь 4, 2024

Purpose This paper aims to critically evaluate the role of advanced artificial intelligence (AI)-enhanced image fusion techniques in lung cancer diagnostics within context AI-driven precision medicine. Design/methodology/approach We conducted a systematic review various studies assess impact AI-based methodologies on accuracy and efficiency diagnosis. The focus was integration AI their application personalized treatment strategies. Findings reveals significant improvements diagnostic precision, crucial aspect evolution healthcare. These substantially enhance diagnosis, thereby influencing approaches. study also explores broader implications these healthcare resource allocation, policy formation, epidemiological trends. Originality/value is notable for both emphasizing clinical importance AI-integrated illuminating profound influence technologies have future systems.

Язык: Английский

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