Colorectal cancer screening:The value of early detection and modern challenges

The screening of colorectal cancer(CRC)is pivotal for both the prevention and treatment of this disease,significantly improving early-stage tumor detection rates.This advancement not only boosts survival rates and quality of life for patients but also reduces the costs associated with treatment.However,the adoption of CRC screening methods faces numerous challenges,including the technical limitations of both noninvasive and invasive methods in terms of sensitivity and specificity.Moreover,socioeconomic factors such as regional disparities,economic conditions,and varying levels of awareness affect screening uptake.The coronavirus disease 2019 pandemic further intensified these challenges,leading to reduced screening participation and increased waiting periods.Additionally,the growing prevalence of early-onset CRC necessitates innovative screening approaches.In response,research into new methodologies,including artificial intelligence-based systems,aims to improve the precision and accessibility of screening.Proactive measures by governments and health organizations to enhance CRC screening efforts are underway,including increased advocacy,improved service delivery,and international cooperation.The role of technological innovation and global health collaboration in advancing CRC screening is undeniable.Technologies such as artificial intelligence and gene sequencing are set to revolutionize CRC screening,making a significant impact on the fight against this disease.Given the rise in early-onset CRC,it is crucial for screening strategies to continually evolve,ensuring their effectiveness and applicability.

Esophageal cancer screening,early detection and treatment:Current insights and future directions

Esophageal cancer ranks among the most prevalent malignant tumors globally,primarily due to its highly aggressive nature and poor survival rates.According to the 2020 global cancer statistics,there were approximately 604000 new cases of esophageal cancer,resulting in 544000 deaths.The 5-year survival rate hovers around a mere 15%-25%.Notably,distinct variations exist in the risk factors associated with the two primary histological types,influencing their worldwide incidence and distribution.Squamous cell carcinoma displays a high incidence in specific regions,such as certain areas in China,where it meets the cost-effect-iveness criteria for widespread endoscopy-based early diagnosis within the local population.Conversely,adenocarcinoma(EAC)represents the most common histological subtype of esophageal cancer in Europe and the United States.The role of early diagnosis in cases of EAC originating from Barrett's esophagus(BE)remains a subject of controversy.The effectiveness of early detection for EAC,particularly those arising from BE,continues to be a debated topic.The variations in how early-stage esophageal carcinoma is treated in different regions are largely due to the differing rates of early-stage cancer diagnoses.In areas with higher incidences,such as China and Japan,early diagnosis is more common,which has led to the advancement of endoscopic methods as definitive treatments.These techniques have demonstrated remarkable efficacy with minimal complications while preserving esophageal functionality.Early screening,prompt diagnosis,and timely treatment are key strategies that can significantly lower both the occurrence and death rates associated with esophageal cancer.

Novel biomarkers for early detection of gastric cancer

Gastric cancer(GC)remains a leading cause of cancer-related death worldwide.Less than half of GC cases are diagnosed at an advanced stage due to its lack of early symptoms.GC is a heterogeneous disease associated with a number of genetic and somatic mutations.Early detection and effective monitoring of tumor progression are essential for reducing GC disease burden and mortality.The current widespread use of semi-invasive endoscopic methods and radiologic approaches has increased the number of treatable cancers:However,these approaches are invasive,costly,and time-consuming.Thus,novel molecular noninvasive tests that detect GC alterations seem to be more sensitive and specific compared to the current methods.Recent technological advances have enabled the detection of blood-based biomarkers that could be used as diagnostic indicators and for monitoring postsurgical minimal residual disease.These biomarkers include circulating DNA,RNA,extracellular vesicles,and proteins,and their clinical applications are currently being investigated.The identification of ideal diagnostic markers for GC that have high sensitivity and specificity would improve survival rates and contribute to the advancement of precision medicine.This review provides an overview of current topics regarding the novel,recently developed diagnostic markers for GC.

Diagnostic value of matrix metalloproteinases 2, 7 and 9 in urine for early detection of colorectal cancer

BACKGROUND A noninvasive biomarker with high diagnostic performance is urgently needed for the early diagnosis of colorectal cancer(CRC).AIM To evaluate the diagnostic value of matrix metalloproteinases(MMPs)2,7 and 9 in urine for CRC.METHODS Of 59 healthy controls,47 patients with colon polyps and 82 patients with CRC were included in this study.Carcinoembryonic antigen(CEA)in serum and MMP2,MMP7,and MMP9 in urine were detected.The combined diagnostic model of the indicators was established by binary logistic regression.The receiver operating characteristic curve(ROC)of the subjects was used to evaluate the independent and combined diagnostic value of the indicators.RESULTS The MMP2,MMP7,MMP9,and CEA levels in the CRC group differed significantly from levels in the healthy controls(P<0.05).The levels of MMP7,MMP9,and CEA also differed significantly between the CRC group and the colon polyps group(P<0.05).The area under the curve(AUC)distinguishing between the healthy control and the CRC patients using the joint model with CEA,MMP2,MMP7 and MMP9 was 0.977,and the sensitivity and specificity were 95.10%and 91.50%,respectively.For early-stage CRC,the AUC was 0.975,and the sensitivity and specificity were 94.30%and 98.30%,respectively.For advanced stage CRC,the AUC was 0.979,and the sensitivity and specificity were 95.70%and 91.50%,respectively.Using CEA,MMP7 and MMP9 to jointly established a model distinguishing the colorectal polyp group from the CRC group,the AUC was 0.849,and the sensitivity and specificity were 84.10%and 70.20%,respectively.For early-stage CRC,the AUC was 0.818,and the sensitivity and specificity were 76.30%and 72.30%,respectively.For advanced stage CRC,the AUC was 0.875,and the sensitivity and specificity were 81.80%and 72.30%,respectively.CONCLUSION MMP2,MMP7 and MMP 9 may exhibit diagnostic value for the early detection of CRC and may serve as auxiliary diagnostic markers for CRC.

Epidemic trend,screening,and early detection and treatment of cancer in Chinese population

Epidemiological studies showed the incidence mortality rates of cancer were increasing in recent decades in Chinese population.National and regional preventive programs aim to reduce the health hazards of cancer and focuse the population at high risks for specific cancer, particularly in rural areas and to offer the access to early detection for multlple cancers in urban areas. The early screening, early detection and treatment have been put into operation for the population at risks in rural areas at first, and in the urban areas in recent years. To understand the epidemic patterns and trends of cancer, and the experiences in applying early detection strategies in China, selected literatures were reviewed for brief summary.

Advances in lung cancer screening and early detection

Lung cancer is associated with a heavy cancer-related burden in terms of patients’physical and mental health worldwide.Two randomized controlled trials,the US-National Lung Screening Trial(NLST)and Nederlands-Leuvens Longkanker Screenings Onderzoek(NELSON),indicated that low-dose CT(LDCT)screening results in a statistically significant decrease in mortality in patients with lung cancer,LDCT has become the standard approach for lung cancer screening.However,many issues in lung cancer screening remain unresolved,such as the screening criteria,high false-positive rate,and radiation exposure.This review first summarizes recent studies on lung cancer screening from the US,Europe,and Asia,and discusses risk-based selection for screening and the related issues.Second,an overview of novel techniques for the differential diagnosis of pulmonary nodules,including artificial intelligence and molecular biomarker-based screening,is presented.Third,current explorations of strategies for suspected malignancy are summarized.Overall,this review aims to help clinicians understand recent progress in lung cancer screening and alleviate the burden of lung cancer.

Early detection of noise-induced hearing loss

BACKGROUND Noise-induced hearing loss(NIHL)is the second most common acquired hearing loss following presbycusis.Exposure to recreational noise and minimal use of hearing protection increase the prevalence of NIHL in young females.NIHL is irreversible.Identifying minor hearing pathologies before they progress to hearing problems that affect daily life is crucial.AIM To compare the advantages and disadvantages of extended high frequency(EHF)and otoacoustic emission and determine an indicator of hearing pathologies at the early sub-clinical stage.METHODS This cross-sectional study was implemented in West China Hospital of Sichuan University from May to September 2019.A total of 86 participants,aged 18-22 years,were recruited to establish normative thresholds for EHF.Another 159 adults,aged 18-25 years with normal hearing(0.25-8 kHz≤25 dBHL),were allocated to low noise and noise exposure groups.Distortion otoacoustic emission(DPOAE),transient evoked otoacoustic emissions(TEOAE),and EHF were assessed in the two groups to determine the superior technique for detecting early-stage noise-induced pathologies.The chi-square test was used to assess the noise and low noise exposure groups with respect to extended high-frequency audiometry(EHFA),DPOAE,and TEOAE.P≤0.05 was considered statistically significant.RESULTS A total of 86 participants(66 females and 20 males)aged between 18 and 22(average:20.58±1.13)years were recruited to establish normative thresholds for EHF.The normative thresholds for 9,10,11.2,12.5,14,16,18,and 20 kHz were 15,10,20,15,15,20,28,and 0 dBHL,respectively.A total of 201 participants were recruited and examined for eligibility.Among them,159 adults aged between 18 and 25 years were eligible in this study.No statistical difference was detected between the noise exposure and the low noise exposure groups using EHFA,DPOAE,and TEOAE(P>0.05)except in the right ear at 4 kHz using TEOAE(abnormal rate 20.4%vs 5.2%,respectively;P=0.05).CONCLUSION These results showed TEOAE as the earliest indicator of minor pathology compared to DPOAE and EHFA.However,a multicenter controlled study or prospective study is essential to verify these results.

Early detection of pancreatic cancer

Pancreatic adenocarcinoma is a low-incident but highly mortal disease. It accounts for only 3% of estimated new cancer cases each year but is currently the fourth common cause of cancer mortality. By 2030, it is expected to be the 2nd leading cause of cancer death. There is a clear need to diagnose and classify pancreatic cancer at earlier stages in order to give patients the best chance at a definitive cure through surgery. Three precursor lesions that distinctly lead to pancreatic adenocarcinoma have been identified, and we have increasing understanding the non-genetic and genetic risk factors for the disease. With increased understanding about the risk factors, the familial patters, and associated accumulation of genetic mutations involved in pancreatic cancer, we know that there are mutations that occur early in the development of pancreatic cancer and that improved genetic risk-based strategies in screening for pancreatic cancer may be possible and successful at saving or prolonging lives. The remaining challenge is that current standards for diagnosing pancreatic cancer remain too invasive and too costly for widespread screening for pancreatic cancer. Furthermore, the promises of noninvasive methods of detection such as blood, saliva, and stool remain underdeveloped or lack robust testing. However, significant progress has been made, and we are drawing closer to a strategy for the screening and early detection of pancreatic cancer.

The difficulties of early detection for infectious disease outbreak in China:A qualitative investigation

Objective： To make intensified analysis upon the existing difficulties in early detection for the infectious diseases outbreak in China and put forward some effective measures to improve it. Methods： Field investigation and in-depth interview were applied in 23 interviewees from different-level CDC. Results：The study findings suggest that although the timeliness of outbreak detection has been improved since SARS epidemic in China, some problems still exist, such as： ① lacking syndrome surveillance; ② report quality of infectious disease should be improved; ③ difficulties of identifying the cases at lower social economic status; ④a definite financial compensation mechanism for the operation of web-based report system is absent; ⑤insufficient information exchange among different branches. Conclusion：Some effective measures must be taken including developing syndrome surveillance system; affording more education and txaining for related staff; increasing payout on surveillance and establishing an information exchange platform for early detection of disease outbreak.

Knowledge Attitude and Practice of General Physicians for Early Detection of Diabetic Nephropathy in Cotonou

Introduction: General physicians can play an important role in the early detection of diabetic nephropathy (DN). Purpose: To assess the levels of general physicians’ knowledge, attitude and practice in terms of early detection of DN in Cotonou. Method: It was a cross-sectional, analytical and descriptive study which was conducted from 1st March 2015 to 30th September 2015. Every general physician working in a health structure in Cotonou who consented to participate in the study was included. We did not included medical specialists and general physicians working in nephrology department. Data were collected through a survey form designed with a score to assess the various items such as: knowledge, attitude and practice. The significance threshold is set to below 0.05. Results: In total, 202 general physicians were included. The average age was 30.9 ± 6.9 years ranging from 24 to 68 years. A male predominance was observed with 2.2 sex ratio. The majority of respondent medical physicians had poor knowledge in 76.2% cases, bad attitudes (61%) and bad practices (64.9%) in terms of early detection of diabetic nephropathy. There was positive impact of continuing medical training focused on diabetic nephropathy on attitudes (p = 0.016) and practices (p = 0.001) of these physicians. Conclusion: Diabetic nephropathy requires particular attention. General physicians’ continuous training is a principal solution.

Applications of artificial intelligence in, early detection of cancer, clinical diagnosis and personalized medicine

Artificial intelligence(AI)refers to the simulation of human intelligence in machines programmed to convert raw input data into decision-making actions,like humans.AI programs are designed to make decisions,often using deep learning and computer-guided programs that analyze and process raw data into clinical decision making for effective treatment.New techniques for predicting cancer at an early stage are needed as conventional methods have poor accuracy and are not applicable to personalized medicine.AI has the potential to use smart,intelligent computer systems for image interpretation and early diagnosis of cancer.AI has been changing almost all the areas of the medical field by integrating with new emerging technologies.AI has revolutionized the entire health care system through innovative digital diagnostics with greater precision and accuracy.AI is capable of detecting cancer at an early stage with accurate diagnosis and improved survival outcomes.AI is an innovative technology of the future that can be used for early prediction,diagnosis and treatment of cancer.

Novel Non-Protein Biomarkers for Early Detection of Hepatocellular Carcinoma

Early detection of hepatocellular carcinoma(HCC)while in its early stages is critical for reducing HCC mortality in high-risk patients.However,highly sensitive and specific surveillance biomarkers for early-stage HCC detection are still lacking.In recent years,great efforts have been made to research tumor-derived molecular features that are detectable in circulation,such as circulating tumor deoxyribonucleic acid and circulating tumor ribonucleic acid,in order to explore their potential as noninvasive biomarker candidates in many tumor types.In this review,we summarize current studies on these new approaches and their application in early HCC detection.

Internet of things-based health monitoring system for early detection of cardiovascular events during COVID-19 pandemic

The coronavirus disease 2019(COVID-19)has currently caused the mortality of millions of people around the world.Aside from the direct mortality from the COVID-19,the indirect effects of the pandemic have also led to an increase in the mortality rate of other non-COVID patients.Evidence indicates that novel COVID-19 pandemic has caused an inflation in acute cardiovascular mortality,which did not relate to COVID-19 infection.It has in fact increased the risk of death in cardiovascular disease(CVD)patients.For this purpose,it is dramatically inevitable to monitor CVD patients’vital signs and to detect abnormal events before the occurrence of any critical conditions resulted in death.Internet of things(IoT)and health monitoring sensors have improved the medical care systems by enabling latency-sensitive surveillance and computing of large amounts of patients’data.The major challenge being faced currently in this problem is its limited scalability and late detection of cardiovascular events in IoT-based computing environments.To this end,this paper proposes a novel framework to early detection of cardiovascular events based on a deep learning architecture in IoT environments.Experimental results showed that the proposed method was able to detect cardiovascular events with better performance(95.30%average sensitivity and 95.94%mean prediction values).

Integrated Random Early Detection for Congestion Control at the Router Buffer

This paper proposed an Integrated Random Early Detection(IRED)method that aims to resolve the problems of the queue-based AQM and loadbased AQM and gain the benefits of both using indicators from both types.The arrival factor(e.g.,arrival rate,queue and capacity)and the departure factors are used to estimate the congestion through two integrated indicators.The utilized indicators are mathematically calculated and integrated to gain unified and coherent congestion indicators.Besides,IRED is built based on a new dropping calculation approach that fits the utilized congestion indicators while maintaining the intended buffer management criteria,avoiding global synchronization and enhancing the performance.The results showed that IRED,compared to RED,BLUE,ERED,FLRED,EnRED and DcRED,decreased packet delay and loss under various network status.Specifically,the results showed that in heavy and moderate traffic,the proposed IRED method outperformed the state-of-the-art methods in loss and delay by 18% and 10.6%,respectively.

A gas kick early detection method outside riser based on Doppler ultrasonic wave during deepwater drilling

The feasibility of gas kick early detection outside the riser was analyzed based on gas-liquid multiphase flow theory.Then an experimental platform for gas kick early detection based on Doppler ultrasonic wave was established and the propagation experiments in two-phase flow of gas-water(sucrose solutions)were conducted.The time and frequency domains of the Doppler ultrasonic wave signals during the experiments were analyzed.The results show that:(1)No matter the pump was on or off,the detected average Doppler ultrasonic signal voltage increased first and then decreased with the increase of the gas void fraction,and had a quadratic function relation with gas void fraction,so the average voltage change of the monitored signals can be used to deduce the approximate gas void fraction.The Doppler ultrasonic wave signal voltage was significantly reduced in magnitude and variation in the solution with higher viscosity,and the viscosity has stronger impact on the magnitude of signal than density.(2)When the pump was stopped,the Doppler shift increased with the increase of gas void fraction,and the two showed a nearly linear relation,so the detected amount of Doppler shift can reflect the variation of gas void fraction quantitatively.When the pump was on,the sound energy produced by frequency converter had a more significant impact on amplitude spectrum than gas void fraction,so it is impossible to determine whether gas kick occurs by frequency domain signal analysis.(3)This method is a non-contact measurement,with no contact with the drilling fluid and no disruption to the drilling operation.It can quantitatively characterize the gas void fraction according to the change of Doppler ultrasonic signal,enabling earlier detection of gas kick.

Role of artificial intelligence in early detection and screening for pancreatic adenocarcinoma

Pancreatic adenocarcinoma remains to be one of the deadliest malignancies in the world despite treatment advancement over the past few decades.Its low survival rates and poor prognosis can be attributed to ambiguity in recommendations for screening and late symptom onset,contributing to its late presentation.In the recent years,artificial intelligence(AI)as emerged as a field to aid in the process of clinical decision making.Considerable efforts have been made in the realm of AI to screen for and predict future development of pancreatic ductal adenocarcinoma.This review discusses the use of AI in early detection and screening for pancreatic adenocarcinoma,and factors which may limit its use in a clinical setting.

Early detection of cardiac allograft vasculopathy and chronic rejection after heart transplantation-Report of one case

Objective To study clinically the feasibility of early diagnosis of cardiac allograft vascularopathy(CAV) and chronic rejection. Methods A 13-year-old female patient with dilated cardiomy-opathy received orthotopic heart transplantation for advanced heart failure, and subsequent immunosuppressive therapy including cyclosporine, prednisone and mofetil, and a mondily close follow-up. Coronary angiography and left ventricular endomyocardial biopsy (EMB) was perormed 9 months after the operation. Results The clinical and follow-up data of the case showed that cardiac or systemic nonspecific symptoms such as exertional chest discomfort, palpitation, fatigue or fever of unknown reasons were the first and ignorable clinical symptoms, and found disappeared after dosage addition of cyclinsporine, which indicated a early clinical manifestations of rejection or vasculopathy. While persistent sinus tachycardia on electrocadiogram, decreased left ventricular ejection fraction(from 64% -68% down to 47% - 50% ),

DNA methylation drives a new path in gastric cancer early detection:Current impact and prospects

Gastric cancer(GC)is one of the most common and deadly cancers worldwide.Early detection offers the best chance for curative treatment and reducing its mortality.However,the optimal population-based early screening for GC remains unmet.Aberrant DNA methylation occurs in the early stage of GC,exhibiting cancer-specific genetic and epigenetic changes,and can be detected in the media such as blood,gastric juice,and feces,constituting a valuable biomarker for cancer early detection.Furthermore,DNA methylation is a stable epigenetic alteration,and many innovative methods have been developed to quantify it rapidly and accurately.Nonetheless,large-scale clinical validation of DNA methylation serving as tumor biomarkers is still lacking,precluding their implementation in clinical practice.In conclusion,after a critical analysis of the recent existing literature,we summarized the evolving roles of DNA methylation during GC occurrence,expounded the newly discovered noninvasive DNA methylation biomarkers for early detection of GC,and discussed its challenges and prospects in clinical applications.

Exploring the Role of Serum Cystatin C in Early Detection of Acute Kidney Injury among On-Pump Cardiac Surgery Patients: A Single-Center Investigation in Bangladesh

Background: Acute Kidney Injury (AKI) stands as a prominent postoperative complication in on-pump cardiac surgery, with repercussions on morbidity, mortality, and hospitalization duration. Current diagnostic criteria relying on serum creatinine levels exhibit a delayed identification of AKI, prompting an exploration of alternative biomarkers. Aims and Objectives: This study is designed to overcome diagnostic constraints and explore the viability of serum Cystatin C as an early predictor of Acute Kidney Injury (AKI) in individuals undergoing on-pump cardiac surgery. The investigation aims to establish the relationship between serum Cystatin C levels and the onset of AKI in patients subjected to on-pump cardiac surgery. Primary objectives involve the assessment of the diagnostic effectiveness of serum Cystatin C, its comparison with serum creatinine, and the exploration of its potential for the early identification and treatment of AKI. Methodology: Conducted as a single-center study at the cardiac surgery department of BSMMU in Bangladesh from September 2020 to August 2022, a comparative cross-sectional analysis involved 31 participants categorized into No AKI and AKI groups based on Kidney Disease: Improving Global Outcomes (KDIGO) criteria. Data collection encompassed preoperative, post-CBP (cardiopulmonary bypass) conclusion at 2 hours, postoperative day 1, and postoperative day 2 intervals. Statistical analyses included Chi-squared tests, independent Student’s t-tests, and one-sample t-tests. Significance was set at P Results: The study revealed no significant differences in baseline characteristics between the No AKI and AKI groups, except for CPB time and cross-clamp time. Serum Cystatin C levels in the AKI group exhibited statistical significance at various time points, highlighting its potential as an early detector. Conversely, Serum Creatinine levels in the AKI group showed no statistical significance. The Receiver Operating Characteristic (ROC) curve analysis further supported the efficacy of serum Cystatin C, with an Area under the ROC Curve of 0.864 and a cut-off value of 0.55 (p Conclusion: This study supports the superior utility of serum Cystatin C as an early detector of AKI in on-pump cardiac surgery patients compared to serum creatinine. Its ability to identify AKI several hours earlier may contribute to reduced morbidity, mortality, and healthcare costs. The findings underscore the significance of exploring novel biomarkers for improved post-cardiac surgery renal function assessment.

Autonomous machine learning for early bot detection in the internet of things

The high costs incurred due to attacks and the increasing number of different devices in the Internet of Things(IoT)highlight the necessity of the early detection of botnets(i.e.,a network of infected devices)to gain an advantage against attacks.However,early botnet detection is challenging because of continuous malware mutations,the adoption of sophisticated obfuscation techniques,and the massive volume of data.The literature addresses botnet detection by modeling the behavior of malware spread,the classification of malicious traffic,and the analysis of traffic anomalies.This article details ANTE,a system for ANTicipating botnEt signals based on machine learning algorithms.The system adapts itself to different scenarios and detects different types of botnets.It autonomously selects the most appropriate Machine Learning(ML)pipeline for each botnet and improves the classification before an attack effectively begins.The system evaluation follows trace-driven experiments and compares ANTE results to other relevant results from the literature over four representative datasets:ISOT HTTP Botnet,CTU-13,CICDDoS2019,and BoT-IoT.Results show an average detection accuracy of 99.06%and an average bot detection precision of 100%.