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Endoscopic optical imaging technologies for the detection and evaluation of dysplasia and early cancer have made great strides in recent decades. With the capacity of in vivo early detection of subtle lesions, they allow modern endoscopists to provide accurate and effective optical diagnosis in real time. This review mainly analyzes the current status of clinically available endoscopic optical imaging techniques, with emphasis on the latest updates of existing techniques. We summarize current coverage of these technologies in major hospital departments such as gastroenterology, urology, gynecology, otolaryngology, pneumology, and laparoscopic surgery. In order to promote a broader understanding, we further cover the underlying principles of these technologies and analyze their performance. Moreover, we provide a brief overview of future perspectives in related technologies, such as computer-assisted diagnosis (CAD) algorithms dealing with exploring endoscopic video data. We believe all these efforts will benefit the healthcare of the community, help endoscopists improve the accuracy of diagnosis, and relieve patients’ suffering.

In the future, early diagnosis of cancers may be performed using labon-a-chip devices. Yet, very little is known about the research obtained so far, who are the leading institutions, and how they c...

Bioimaging and biosensing have garnered interest in early cancer diagnosis due to the ability of gaining in-depth insights into cellular functions and providing a wide range of diagnostic parameters. Emerging 2D materials of multielement MXenes and monoelement black phosphorous nanosheets (BPNSs) with unique intrinsic physicochemical properties such as a tunable bandgap and layer-dependent fluorescence, high carrier mobility and transport anisotropy, efficient fluorescence quenching capability, desirable light absorption and thermoelastic properties, and excellent biocompatibility and biosafety properties provide promising nano-platforms for bioimaging and biosensing applications. In view of the growing attention on the rising stars of the post-graphene age in the progress of bioimaging and biosensing, and their common feature characteristics as well as complementarity for constructing complexes, the main objective of this review is to reveal the recent advances in the design of MXene or BPNS based nanoplatforms in the field of bioimaging and biosensing. The preparation and surface functionalization methods, biosafety, and other important aspects of bioimaging and biosensing applications of MXenes and BPNSs have been assessed systematically, along with highlighting the main challenges in further biomedical application. The review not only focuses on the advancements in 2D materials for use in bioimaging and biosensing but also assesses the possibility of their future potential in bioapplications.

The role of altered tissue mechanics in early cancer development is not well understood. A new study reveals how oncogene activation generates force within a tissue to impact cell division in surrounding normal cells, which then contribute to tumour formation.

PURPOSE Globally, breast cancer represents the most common cause of cancer death among women. Early cancer diagnosis is difficult in low- and middle-income countries, most of which are unable to support population-based mammographic screening. Triage on the basis of clinical breast examination (CBE) alone can be difficult to implement. In contrast, piezo-electric palpation (intelligent Breast Exam [iBE]) may improve triage because it is portable, low cost, has a short learning curve, and provides electronic documentation for additional diagnostic workup. We compared iBE and CBE performance in a screening patient cohort from a Western mammography center. METHODS Women presenting for screening or diagnostic workup were enrolled and underwent iBE then CBE, followed by mammography. Mammography was classified as negative (BI-RADS 1 or 2) or positive (BI-RADS 3, 4, or 5). Measures of accuracy and κ score were calculated. RESULTS Between April 2015 and May 2017, 516 women were enrolled. Of these patients, 486 completed iBE, CBE, and mammography. There were 101 positive iBE results, 66 positive CBE results, and 35 positive mammograms. iBE and CBE demonstrated moderate agreement on categorization (κ = 0.53), but minimal agreement with mammography (κ = 0.08). iBE had a specificity of 80.3% and a negative predictive value of 94%. In this cohort, only five of 486 patients had a malignancy; iBE and CBE identified three of these five. The two cancers missed by both modalities were small—a 3-mm retro-areolar and a 1-cm axillary tail. CONCLUSION iBE performs comparably to CBE as a triage tool. Only minimal cancers detected through mammographic screening were missed on iBE. Ultimately, our data suggest that iBE and CBE can synergize as triage tools to significantly reduce the numbers of patients who need additional diagnostic imaging in resource-limited areas.

Objective: Because of the increased precision of ultrasound breast cancer screening, early cancer cases with no clear mass or extraction of microcysts on imaging have recently increased, and improvement of the accuracy of breast fine-needle aspiration biopsy (FNAB) cytology is needed. The objective of this study was to investigate the usefulness of cluster gray image-fractal analysis evaluating the darkness of clusters, cluster unevenness, and complexity of hyperchromicity (cluster density) of deep-stained cell clusters, known as hyperchromatic crowded cell groups (HCG), on FNAB as a cytology assistance system for breast FNAB. Study Design: One hundred clusters collected from 10 patients with fibroadenoma (FA), 90 clusters from 9 patients with ductal carcinoma in situ (DCIS), and 122 clusters from 11 patients with invasive breast carcinoma of no special type (IBC-NST) were used. (1) Cluster size classification: clusters were classified into small, middle, and large clusters (small cluster: smaller than 40 × 102 μm2; large cluster: 100 × 102 μm2 or larger; middle cluster: intermediate), and their frequency was calculated. (2) Cluster gray image-fractal analysis: (a) the darkness of clusters (luminance), (b) cluster unevenness (complexity), and (c) complexity of cluster density (roundness-corrected fractal value) were assessed. For statistical analysis, the multiple comparison Steel-Dwass test was used, with a significance level of p < 0.05. Results: (1) Cluster size classification: in FA, small, middle, and large clusters appeared at a similar frequency, and the frequency (30%) of large clusters was significantly higher than that in other diseases. In IBC-NST, many small clusters (61%) appeared and their frequency was significantly higher than that in other diseases, whereas the frequency of large clusters was significantly lower. (2) Cluster gray image-fractal analysis: in IBC-NST, the luminance of small clusters was low (dark), the cluster unevenness was high, and the complexity of cluster density was high, whereas the luminance of large clusters was high (bright), the cluster unevenness was high, and complexity of cluster density was high compared with those in FA. Conclusion: Cluster gray image-fractal analysis evaluating the darkness of clusters, cluster unevenness, and complexity of cluster density in breast FNAB HCG is a useful cytology assistance system for breast FNA.

Early Barrett’s neoplasia are often missed due to subtle visual features and inexperience of the non-expert endoscopist with such lesions. While promising results have been reported on the automated detection of this type of early cancer in still endoscopic images, video-based detection using the temporal domain is still open. The temporally stable nature of video data in endoscopic examinations enables to develop a framework that can diagnose the imaged tissue class over time, thereby yielding a more robust and improved model for spatial predictions. We show that the introduction of Recurrent Neural Network nodes offers a more stable and accurate model for tissue classification, compared to classification on individual images. We have developed a customized Resnet18 feature extractor with four types of classifiers: Fully Connected (FC), Fully Connected with an averaging filter (FC Avg (n = 5)), Long Short Term Memory (LSTM) and a Gated Recurrent Unit (GRU). Experimental results are based on 82 pullback videos of the esophagus with 46 high-grade dysplasia patients. Our results demonstrate that the LSTM classifier outperforms the FC, FC Avg (n = 5) and GRU classifier with an average accuracy of 85.9% compared to 82.2%, 83.0% and 85.6%, respectively. The benefit of our novel implementation for endoscopic tissue classification is the inclusion of spatio-temporal information for improved and robust decision making, and it is the first step towards full temporal learning of esophageal cancer detection in endoscopic video.

Detection of circulating tumor cells (CTC) is an important liquid biopsy technique that has advanced considerably in recent years. To further advance the development of technology for curing cancer, several CTC technologies have been proposed by various research groups. Despite their potential role in early cancer diagnosis and prognosis, CTC methods are currently used for research purposes only, and very few methods have been accepted for clinical applications because of difficulties, including CTC heterogeneity, CTC separation from the blood, and a lack of thorough clinical validation. Although current CTC technologies have not been truly implemented, they possess high potential as future clinical diagnostic techniques for individualized cancer. Here, we review current developments in CTC separation technology. We also explore new CTC detection methods based on telomerase and nanomaterials, such as in vivo flow cytometry. In addition, we discuss the difficulties that must be overcome before CTC can be applied in clinical settings.

The study aims to evaluate the eff ectiveness of standard and modifi ed settings of the spectral color allocation technology in the diff erential diagnosis of the colon morphological type of epithelial formations. Materials and methods: video colonoscopy using standard and modifi ed mode of technology. A total of 746 patients were selected for spectral colour selection, of whom 80 were selected. There were 36 men, 44 women. The average age of the patients was 60 ± 9 years. There were 171 epithelial fomations, of which 106 (61.9%) were located in the left side of the large intestine: in the rectum — 33 (31.2%), in sigmoid — 52 (49%), in descending part — 21 (19.8%). In the right parts of the colon there were significant lower number of formations — 65 (38.1%): ascending intestine — 26 (40%), transversely — colon — 32 (49.2%), cecum — 7 (10.8%). Endoscopic studies were performed according to standard method using video colonoscopes from Fujinon, EC-590ZW / L, EC-530WL. Results: statistically revealed that the probability of determining the correct morphological type of epithelium is formation is 6 times higher when using the modifi ed spectral color technology highlight compared to standard technology settings. Conclusion: the modifi ed settings of the technology of spectral color highlighting allow much more accurative performance an optical biopsy of epithelial colon formations.

Background Exosomes are small vesicles produced by almost all cells in the body and found in all biofluids. Cancer cell-derived exosomes are known to have distinct, measurable signatures, applicable for early cancer diagnosis. Despite the present bibliometric studies on "Cancer detection" and "Nanoparticles", no single study exists to deal with "Exosome" bibliometric study. Methods This bibliometric work investigated the publication trends of "Exosomes" nanoparticles and its application in cancer detection, for the literature from 2008 to July 2019. The data were collected from the Web of Science Core Collection. There were variant visual maps generated to show annual publication, most- relevant authors, sources, countries, topics and keywords. The network analysis of these studies was investigated to evaluate the research trends in the field of exosomes. In addition, the data were qualitatively analyzed according to 22 top-cited articles, illustrating the frequently used subjects and methods in exosomes research area. Results The results showed that the documents in this field have improved the citation rate. The top-relevant papers are mostly published in Scientific Reports journal which has lost its popularity after 2017, while today, Analytical Chemistry is leading in publishing the most articles related to exosomes. The documents containing keywords of plasma, cells, cancer, biomarkers, and vesicles as keywords plus, are more likely to be published in PLoS One journal. The clustering of the keywords network showed that the keyword theme of "extracellular vesicles" has the highest centrality rate. In global research, USA is the most corresponding country, followed by China, Korea and Australia. Based on the qualitative analysis, the published documents with at least 50 citations have used exosome release, cargo, detection, purification and secretion, as their targets and applied cell culture or isolation as their methods. Conclusion The bibliometric study on exosomes nanoparticles for cancer detection provides a clear vision of the future research direction and identifies the potential opportunities and challenges. This may lead new researchers to select the proper subfields in exosome-related research fields.

Recently, circulating microRNAs (miRNAs) in body fluids have been reported as one of cancer diagnostic biomarkers, and detection of miRNAs is expected to improve early cancer diagnosis. In this stu...

Purpose Diagnosing cancer early is an imperative, as help-seeking delays affect survival. Quality of life (QoL) deteriorates after diagnosis, but decline may start when cancer is suspected at the earliest stage of the pathway to treatment. This study examined whether offering guided feedback about personal QoL to adults with potential cancer symptoms, living in deprived communities, changes QoL and promotes help-seeking in primary care. Methods Visitors to a CRUK mobile cancer roadshow were recruited in 43 sites. A prospective longitudinal (2 × 2) repeated-measures design was applied. Where they presented a potential cancer symptom, and were ‘signposted’ to a GP, they were allocated to a symptom condition, or a lifestyle condition, if seeking cancer risk advice. Randomisation was to an Intervention group, who received feedback about personal QoL results (WHOQOL-BREF and WHOQOL importance measures), or a Control group who assessed QoL without feedback. Depression was screened. Results Of 107 participants, the mean age was 53; 50% were women, 57% were without tertiary education, 66% were unemployed and 45% were currently ill. Over 10 weeks, 54% of all those with symptoms sought help from a medical source and 42% specifically from a GP. Thirty-one completed all three assessments. With symptoms present, psychological, social and environmental QoL were poor, becoming poorer over time. When the symptoms group received feedback, psychological QoL increased, but GP visits were unaffected. However, feedback increased help-seeking from informal social contacts. Lifestyle groups reported consistently good psychological and social QoL. Conclusion This early cancer research offers practical and theoretical implications for QoL interventions in deprived communities.

Sentinel lymph node biopsy (SLNB) has become the standard staging technique in the surgical treatment of breast cancer, replacing the older method of dissecting lymph nodes of the axilla. Several advantages like lowering of the morbidities that accompany the technique and being less invasive have given rise to a promising effect on life aspects of patients suffering from this morbidity. The procedure has evolved over the last few decades, but further studies are still needed to make improvements. Several aspects of the evolution of SLNB, such as the incorporation of the management in early cancer, the technique of lymphatic mapping, the accuracy of the technique, and its utility and evaluation in clinical response after neoadjuvant chemotherapy are discussed in this review.

Monitoring of over-expressed nucleolin in the cytoplasm facilitates early cancer diagnosis. Herein, we present a novel biosensing nanoscaffold based on anti-nucleolin aptamers and polymer-grafted graphene oxides for the fluorescent imaging of nucleolin in the cell cytoplasm, which can distinguish cancer cells from normal cells.

Liquid biopsy has emerged in the last ten years as an appealing noninvasive strategy to support early cancer diagnosis and follow-up interventions. However, conventional liquid biopsy strategies involving specified biomarkers have encountered unexpected inconsistencies stemming from the use of different analytical methodologies. Recent reports have repeatedly demonstrated that integrated detection of multiple liquid biopsy biomarkers can significantly improve diagnostic performance by eliminating the influence of intratumoral heterogeneity. Herein, we review the progress in the field of liquid biopsy and propose a novel integrated liquid biopsy framework consisting of three categories: elementary, intermediate, and advanced integration. We also summarize the merits of the integration strategy and propose a roadmap toward refining cancer diagnosis, metastasis surveillance, and prognostication.

Traditional cancer diagnosis strategies are not considered by most people until the last resort, which delays many cancer treatments leading to advanced stages. Tumor marker sensors show great potential for detecting cancer because of its cost-effective and harmless checking procedures. Normally, one tumor marker is detected each time by using one type of sensor, but the accuracy to declare cancer is not always satisfied. Metal nanoclusters are ultra-small nanomaterials with low toxicity, distinct optical properties, catalytic activities, and cost-effective performance. Some metal nanoclusters have been designed to detect more than one tumor marker in a single step. The consideration of combined parameters using such facile sensing strategies has the potential to simplify the test procedure, and increase the diagnostic accuracy of early cancer. Therefore, various sensing strategies for the multiplex detection of tumor markers using metal nanoclusters are summarized.

The early diagnoses of esophageal cancer are of great significance in the clinic because they are critical for reducing mortality. At present, the diagnoses are mainly performed by artificial detection and annotations based on gastroscopic images. However, these procedures are very challenging to clinicians due to the large variability in the appearance of early cancer lesions. To reduce the subjectivity and fatigue in manual annotations and to improve the efficiency of diagnoses, computer-aided annotation methods are highly required. In this work, we proposed a novel method that utilized deep learning (DL) techniques to realize the automatic annotation of early esophageal cancer (EEC) lesions in gastroscopic images. The depth map of gastroscopic images was initially extracted by a DL network. Then, this additional depth information was fused with the original RGB gastroscopic images, which were then sent to another DL network to obtain precise annotations of EEC regions. In total, 4231 gastroscopic images of 732 patients were used to build and validate the proposed method. A total of 3190 of those images were EEC images, and the remaining 1041 were non-EEC images. The experimental results show that the combination of depth information and RGB information improved the annotation performance. The final EEC detection rate and mean Dice Similarity Coefficient (DSC) of our method were 97.54% and 74.43%, respectively. Compared with other state-of-the-art DL-based methods, the proposed method showed better annotation performances and fewer false positive outputs. Therefore, our method offers a good prospect in aiding the clinical diagnoses of EEC.

Lung cancer is one of the malignant tumor diseases with the fastest increase in morbidity and mortality, which poses a great threat to human health. Low-Dose Computed Tomography (LDCT) screening has been proved as a practical technique for improving the accuracy of pulmonary nodule detection and classification at early cancer diagnosis, which helps to reduce mortality. Therefore, with the explosive growth of CT data, it is of great clinical significance to exploit an effective Computer-Aided Diagnosis (CAD) system for radiologists on automatic nodule analysis. In this article, a comprehensive review of the application and development of CAD systems is presented. The experimental benchmarks for nodule analysis are first described and summarized, covering public datasets of lung CT scans, commonly used evaluation metrics and various medical competitions. We then introduce the main structure of a CAD system and present some efficient methodologies. For the extensive use of Convolutional Neural Network (CNN) based methods in pulmonary nodule investigations recently, we summarized the advantages of CNNs over traditional image processing methods. Besides, we mainly select the CAD systems developed by state-of-the-art CNNs with excellent performance and analyze their objectives, algorithms as well as results. Finally, research trends, existing challenges, and future directions in this field are discussed.

Multifunctional theranostic nanoprobes integrated with stimuli-responsive imaging and therapeutic capabilities have shown great potential to enhance the early cancer diagnostic efficacy and therapeutic efficiency. Elevated levels of lactate and hydrogen peroxide have been considered as the characteristic feature of the tumor microenvironment and can thus be exploited for developing promising theranostic strategies. We demonstrate here that the biocompatible and responsive enzyme-based nanogel probe has been designed as a promising theranostic tool to target high lactate and hydrogen peroxide for ultrasound imaging (US) and cancer treatment. We encapsulate the dual enzyme lactate oxidase (LOD) and catalase (CAT) into the self-assembled nanogels to fabricate responsive nanoprobe LOD/CAT-loaded nanogels (LCNGs). The nanoprobes can respond to the lactate and H

Chronic kidney disease (CKD) is a leading public health problem affecting almost 700 million people globally and is the 12th leading cause of death worldwide.1 The increasing burden of CKD across the globe parallels the increase in ageing populations and the growing prevalence of vascular comorbid conditions like diabetes and hypertension. CKD is associated with increased morbidity and mortality, with patients experiencing an increased risk of death from related conditions such as heart disease and cancers. In 2017, CKD alone resulted in 1.2 million deaths universally.1 Additionally, 1.4 million deaths from cardiovascular disease were attributed to impaired kidney function. CKD is associated with multiple comorbidities which adversely impacts on the life of affected persons and results in reduced quality of life (QoL) compared to the general population,2 with a trend for the lowest QoL experienced by those with kidney failure requiring dialysis.3 Utilities are the numerical value attached to the strength of an individual's preference for specific health-related outcomes. Utility is measured on a 0 to 1 scale, where 0 represents death and 1 represents full health.3 While previous studies have assessed QoL measures in CKD, few have examined domain-specific data in detail across a wide spectrum of CKD stages. Knowledge of factors that negatively affect QoL in CKD may help inform the development of targeted interventions and health policies to help improve QoL in this population. Impaired kidney function is an independent risk factor for cardiovascular disease and all cause mortality, particularly in those with kidney failure requiring dialysis. Kidney transplantation remains the treatment of choice for most patients with kidney failure and is associated with improved survival and QoL compared with treatment with dialysis. However, kidney transplantation is associated with an increased risk of multiple complications through exposure to chronic immunosuppression, with cancer now the leading cause of death in this population.4 Although clinical practice guidelines recommend age and sex-specific screening for potential kidney transplant recipients, cancers ensuing early post-transplant may occur. The incidence and clinical outcomes of these cancers remain uncertain. Knowledge of the epidemiology of these cancers and their risk factors for adverse outcomes will help identify those patients at high risk for developing early cancers post-transplant and facilitate appropriate interventions such as targeted cancer screening in this at-risk population. The aims of this thesis are two-fold. Firstly, we aimed to compare the overall and domain specific QoL in a large cohort of patients with different stages of CKD (stage 3-5, dialysis and kidney transplant recipients) and determine the factors associated with reduced QoL. Secondly, we aimed to compare the burden, frequency, type, stages of cancers and risk of mortality with cancer that occurred early (12 months) after kidney transplantation. Chapter 1 describes and quantifies the disease burden of patients with kidney disease. Chapter 2 reports the QoL experienced by people with CKD, across a broad spectrum of CKD stages and explores overall and domain-specific QoL measures and factors associated with decrements in QoL. Chapter 3 reports the burden of early cancers (occurring

Objective: Raising cancer awareness among adolescents should lead to early diagnosis and improve their survival rate into adulthood. This study aims to identify knowledge of cancer risk factors, symptoms and barriers to seek medical help among Omani adolescents. Methods: A cross-sectional study with Omani adolescents (aged 15-17 years) has been conducted in six schools in Muscat, the capital of Oman. The general Cancer Awareness Measure questionnaire was used to collect the data. Results: A total of 481 adolescents participated. The average recognition of cancer risk factors and symptoms was low (36.8% and 39.6%, respectively). Cancer risk factors and/or symptoms significantly recognised more in girls compared to boys (χ2 = 10.136; Odds ratio [OR] = 2.13 ; 95% confidence interval [CI]= 0.33-3.41; P = 0.001); older (age 17 year) versus younger (aged 15 and 16 years) (χ2 = 6.075; OR = 11.68; 95% CI: 1.11-2.53; P = 0.014); those with existing co-morbidities compared to those without (χ2 = 4.955; OR = 0.41; 95% CI: 0.18-0.92; P = 0.026); and those who knew someone with cancer compared to those who did not (χ2 = 15.285; OR 2.70; 95% CI: 1.62-4.49; P

Effective polymerase chain reactions (PCR) are important in bio-laboratories. It is essential to detect rare DNA-sequence variants for early cancer diagnosis or for drug-resistance mutations identification. Some of the common detection quantitative PCR (qPCR) methods are restricted in the limit of detection (LoD) because of the high polymerase misincorporation rate in Taq DNA polymerases. High-fidelity (HiFi) DNA polymerases have a 50- to 250-fold higher fidelity. Yet, there are currently no proper designs for multiplexed HiFi qPCR reactions. Moreover, the popularity of targeting highly multiplex DNA sequences requires minimizing PCR side products, as the potential of dimerization grows quadratically as the plexes of primers increases. Efforts tried before were either an add-on step, or technology-specific, or requiring high-level computing skills. There lacks an easy-to-apply and cost-effective method for dimerization reduction. Here, we presented the Occlusion System, composed of a 59-overhanged primer and a probe with a short-stem hairpin. We demonstrated that it allowed multiplexing high-fidelity qPCR reaction, it was also compatible with the current variant-enrichment method to improve the LoD by 10-fold. Further, we found that the Occlusion System reduced the dimerization up to 10-fold in highly multiplexed PCR. Thus, the Occlusion System satisfactorily improved both qPCR sensitivity and PCR efficiency.

Early cancer diagnosis is a crucial element to improved treatment options and survival. Great research efforts have been made in the search for better performing cancer diagnostic biomarkers. However, the quest continues as novel biomarkers with high accuracy for an early diagnosis remain an unmet clinical need. Nucleases, which are enzymes capable of cleaving nucleic acids, have been long considered as potential cancer biomarkers. The implications of nucleases are key for biological functions, their presence in different cellular counterparts and catalytic activity led the enthusiasm towards investigating the role of nucleases as promising cancer biomarkers. However, the most essential feature of these proteins, which is their enzymatic activity, has not been fully exploited. This review discusses nucleases interrogated as cancer biomarkers, providing a glimpse of their physiological roles. Moreover, it highlights the potential of harnessing the enzymatic activity of cancer-associated nucleases as a novel diagnostic biomarker using nucleic acid probes as substrates. Funding Agencies|Knut and Alice Wallenberg FoundationKnut & Alice Wallenberg Foundation; Swedish Government Strategic Research Area in Materials Science on Advanced Functional Materials at Linkoping University (Faculty Grant SFO-Mat-LiU) [2009-00971]; Linkoping University

Pancreatic ductal adenocarcinoma (PDAC) is one of the leading causes of cancer deaths worldwide(1). Studies in human tissues and in mouse models have suggested that for many cancers, stem cells sustain early mutations driving tumour development(2,3). For the pancreas, however, mechanisms underlying cellular renewal and initiation of PDAC remain unresolved. Here, using lineage tracing from the endogenous telomerase reverse transcriptase (Tert) locus, we identify a rare TERT-positive subpopulation of pancreatic acinar cells dispersed throughout the exocrine compartment. During homeostasis, these TERT(high) acinar cells renew the pancreas by forming expanding clones of acinar cells, whereas randomly marked acinar cells do not form these clones. Specific expression of mutant Kras in TERT(high) acinar cells accelerates acinar clone formation and causes transdifferentiation to ductal pre-invasive pancreatic intraepithelial neoplasms by upregulating Ras–MAPK signalling and activating the downstream kinase ERK (phospho-ERK). In resected human pancreatic neoplasms, we find that foci of phospho-ERK-positive acinar cells are common and frequently contain activating KRAS mutations, suggesting that these acinar regions represent an early cancer precursor lesion. These data support a model in which rare TERT(high) acinar cells may sustain KRAS mutations, driving acinar cell expansion and creating a field of aberrant cells initiating pancreatic tumorigenesis.

In normal epithelium, mutant clones compete with emerging tumors for space and survival, helping to curb early cancer development. In normal epithelium, mutant clones compete with emerging tumors for space and survival, helping to curb early cancer development.

Cervical screening is an important intervention in the detection and management of early cancer. The global situation regarding cervical cancer is briefly discussed and a family physician’s approach to the procedure and the response to laboratory findings is documented.

With the advent of the big data era, the application of artificial intelligence represented by deep learning in medicine has become a hot topic. In gastroenterology, deep learning has accomplished remarkable accomplishments in endoscopy, imageology, and pathology. Artificial intelligence has been applied to benign gastrointestinal tract lesions, early cancer, tumors, inflammatory bowel diseases, livers, pancreas, and other diseases. Computer-aided diagnosis significantly improve diagnostic accuracy and reduce physicians' workload and provide a shred of evidence for clinical diagnosis and treatment. In the near future, artificial intelligence will have high application value in the field of medicine. This paper mainly summarizes the latest research on artificial intelligence in diagnosing and treating digestive system diseases and discussing artificial intelligence's future in digestive system diseases. We sincerely hope that our work can become a stepping stone for gastroenterologists and computer experts in artificial intelligence research and facilitate the application and development of computer-aided image processing technology in gastroenterology.

Simple Summary Cancer is a leading cause of death worldwide, with the detection of the disease in its early stages, as well as a correct assessment of the tumour margins, being paramount for a successful recovery. While breast cancer is one of most common types of cancer, head and neck cancer is one of the types of cancer with a lower prognosis and poor aesthetic results. Vibrational spectroscopy detects molecular vibrations, being sensitive to different sample compositions, even when the difference was slight. The use of spectroscopy in biomedicine has been extensively explored, since it allows a broader assessment of the biochemical fingerprint of several diseases. This literature review covers the most recent advances in breast and head and neck cancer early diagnosis and intraoperative margin assessment, through Raman and Fourier transform infrared spectroscopies. The rising field of spectral histopathology was also approached. The authors aimed at expounding in a more concise and simple way the challenges faced by clinicians and how vibrational spectroscopy has evolved to respond to those needs for the two types of cancer with the highest potential for improvement regarding an early diagnosis, surgical margin assessment and histopathology. Abstract In 2020, approximately 10 million people died of cancer, rendering this disease the second leading cause of death worldwide. Detecting cancer in its early stages is paramount for patients’ prognosis and survival. Hence, the scientific and medical communities are engaged in improving both therapeutic strategies and diagnostic methodologies, beyond prevention. Optical vibrational spectroscopy has been shown to be an ideal diagnostic method for early cancer diagnosis and surgical margins assessment, as a complement to histopathological analysis. Being highly sensitive, non-invasive and capable of real-time molecular imaging, Raman and Fourier transform infrared (FTIR) spectroscopies give information on the biochemical profile of the tissue under analysis, detecting the metabolic differences between healthy and cancerous portions of the same sample. This constitutes tremendous progress in the field, since the cancer-prompted morphological alterations often occur after the biochemical imbalances in the oncogenic process. Therefore, the early cancer-associated metabolic changes are unnoticed by the histopathologist. Additionally, Raman and FTIR spectroscopies significantly reduce the subjectivity linked to cancer diagnosis. This review focuses on breast and head and neck cancers, their clinical needs and the progress made to date using vibrational spectroscopy as a diagnostic technique prior to surgical intervention and intraoperative margin assessment.

Background To study the application value of narrow-band image international colorectal endoscopic (NICE) classification under non-magnifying endoscopy in the accuracy of colorectal polyp judgment and clarify the learning curve of NICE classification application of endoscopes with different experiences Methods 1674 pictures of colorectal polyps from the Sixth Affiliated Hospital of Sun Yat-sen University from December 2019 to April 2020 were collected. Three junior physicians and one senior physician were respectively used for NICE classification. Pathological diagnosis was taken as the gold standard, and the accuracy rate was calculated and the learning curve was drawn Results The accuracy of NICE classification was 88% and 95.6%, respectively, for primary and senior physicians. The accuracy rates of primary and senior physicians in the diagnosis of inflammatory hyperplasia and invasive cancer were 87.4% and 84%, 99.2%, and 100%, respectively, with no statistically significant difference (P > 0.05). The accuracy of adenoma and early cancer was 63.2% and 90.7%, respectively, with a statistically significant difference (P Conclusions The overall accuracy of NICE classification for colorectal polyps under non-magnifying endoscopy is high, and endoscopists can achieve high accuracy after learning and accumulating a certain number of endoscopic images, which is easy for clinical promotion

High-grade dysplasia carries significant risk of transformation to hepatocellular carcinoma (HCC). Despite this, at the current standard of care, all non-malignant hepatic nodules including high-grade dysplastic nodules are managed similarly. This is partly related to difficulties in distinguishing high-risk pathology in the liver. We aimed to identify chromosome arm-level somatic copy number alterations (SCNAs) that characterise the transition of liver nodules along the cirrhosis-dysplasia-carcinoma axis. We validated our findings on an independent cohort using blood-derived cell-free DNA. A repository of non-cancer DNA sequences obtained from patients with HCC (n = 389) was analysed to generate cut-off thresholds aiming to minimise false-positive SCNAs. Tissue samples representing stages from the multistep process of hepatocarcinogenesis (n = 184) were subjected to low-pass whole genome sequencing. Chromosome arm-level SCNAs were identified in liver cirrhosis, dysplastic nodules, and HCC to assess their discriminative capacity. Samples positive for 1q+ or 8q+ arm-level duplications were likely to be either HCC or high-grade dysplastic nodules as opposed to low-grade dysplastic nodules or cirrhotic tissue with an odds ratio (OR) of 35.5 (95% CI 11.5-110) and 16 (95% CI 6.4-40.2), respectively (p

ObjectiveArtificial intelligence (AI) may reduce underdiagnosed or overlooked upper GI (UGI) neoplastic and preneoplastic conditions, due to subtle appearance and low disease prevalence. Only disease-specific AI performances have been reported, generating uncertainty on its clinical value.DesignWe searched PubMed, Embase and Scopus until July 2020, for studies on the diagnostic performance of AI in detection and characterisation of UGI lesions. Primary outcomes were pooled diagnostic accuracy, sensitivity and specificity of AI. Secondary outcomes were pooled positive (PPV) and negative (NPV) predictive values. We calculated pooled proportion rates (%), designed summary receiving operating characteristic curves with respective area under the curves (AUCs) and performed metaregression and sensitivity analysis.ResultsOverall, 19 studies on detection of oesophageal squamous cell neoplasia (ESCN) or Barrett's esophagus-related neoplasia (BERN) or gastric adenocarcinoma (GCA) were included with 218, 445, 453 patients and 7976, 2340, 13 562 images, respectively. AI-sensitivity/specificity/PPV/NPV/positive likelihood ratio/negative likelihood ratio for UGI neoplasia detection were 90% (CI 85% to 94%)/89% (CI 85% to 92%)/87% (CI 83% to 91%)/91% (CI 87% to 94%)/8.2 (CI 5.7 to 11.7)/0.111 (CI 0.071 to 0.175), respectively, with an overall AUC of 0.95 (CI 0.93 to 0.97). No difference in AI performance across ESCN, BERN and GCA was found, AUC being 0.94 (CI 0.52 to 0.99), 0.96 (CI 0.95 to 0.98), 0.93 (CI 0.83 to 0.99), respectively. Overall, study quality was low, with high risk of selection bias. No significant publication bias was found.ConclusionWe found a high overall AI accuracy for the diagnosis of any neoplastic lesion of the UGI tract that was independent of the underlying condition. This may be expected to substantially reduce the miss rate of precancerous lesions and early cancer when implemented in clinical practice.

Extracellular vesicles (EVs) are small vesicles secreted by various cell types to mediate cell-to-cell communication through the transfer of macromolecules. EVs carry multiple cargo molecules that reflect the origins of their donor cells; thus, they can be considered reliable biomarkers for early cancer diagnosis. However, the diverse cellular origin of EV masks the detection signals generated by both tumor- and nontumor-derived cells. Thereby, the capability to recognize the cellular origin of EVs is the prerequisite for their diagnostic applications. In the present study, we develop an intelligent probabilistic system for tracing the cellular origin of individual EVs using single-molecule multicolor imaging. Through the analysis of the expression profile of two typical membrane protein markers, CD9 and CD63, on single EVs, accurate and rapid probabilistic recognition of EVs derived from individual tumor and nontumor cells in clinical samples is achieved. The correlation between cellular origin and surface protein phenotyping on single EVs is also exemplified. The proposed system holds great potential for advancing EVs as reliable clinical indicators and exploring their biological functions.