Novel automated non-invasive detection of ocular surface squamous neoplasia using artificial intelligence

Ocular surface squamous neoplasia(OSSN)is a common eye surface tumour,characterized by the growth of abnormal cells on the ocular surface.OSSN includes invasive squamous cell carcinoma(SCC),in which tumour cells penetrate the basement membrane and infiltrate the stroma,as well as non-invasive conjunctival intraepithelial neoplasia,dysplasia,and SCC in-situ thereby presenting a challenge in early detection and diagnosis.Early identification and precise demarcation of the OSSN border leads to straightforward and curative treatments,such as topical medicines,whereas advanced invasive lesions may need orbital exenteration,which carries a risk of death.Artificial intelligence(AI)has emerged as a promising tool in the field of eye care and holds potential for its application in OSSN management.AI algorithms trained on large datasets can analyze ocular surface images to identify suspicious lesions associated with OSSN,aiding ophthalmologists in early detection and diagnosis.AI can also track and monitor lesion progression over time,providing objective measurements to guide treatment decisions.Furthermore,AI can assist in treatment planning by offering personalized recommendations based on patient data and predicting the treatment response.This manuscript highlights the role of AI in OSSN,specifically focusing on its contributions in early detection and diagnosis,assessment of lesion progression,treatment planning,telemedicine and remote monitoring,and research and data analysis.

Progress in non-invasive detection of liver fibrosis

Liver fibrosis is an important pathological precondition for hepatocellular carcinoma.The degree of hepatic fibrosis is positively correlated with liver cancer.Liver fibrosis is a series of pathological and physiological process related to liver cell necrosis and degeneration after chronic liver injury,which finally leads to extracellular matrix and collagen deposition.The early detection and precise staging of fibrosis and cirrhosis are very important for early diagnosis and timely initiation of appropriate therapeutic regimens.The risk of severe liver fibrosis finally progressing to liver carcinoma is>50%.It is known that biopsy is the gold standard for the diagnosis and staging of liver fibrosis.However,this method has some limitations,such as the potential for pain,sampling variability,and low patient acceptance.Furthermore,the necessity of obtaining a tissue diagnosis of liver fibrosis still remains controversial.An increasing number of reliable non-invasive approaches are now available that are widely applied in clinical practice,mostly in cases of viral hepatitis,resulting in a significantly decreased need for liver biopsy.In fact,the noninvasive detection and evaluation of liver cirrhosis now has good accuracy due to current serum markers,ultrasound imaging,and magnetic resonance imaging quantification techniques.A prominent advantage of the non-invasive detection and assessment of liver fibrosis is that liver fibrosis can be monitored repeatedly and easily in the same patient.Serum biomarkers have the advantages of high applicability(>95%)and good reproducibility.However,their results can be influenced by different patient conditions because none of these markers are liver-specific.The most promising techniques appear to be transient elastography and magnetic resonance elastography because they provide reliable results for the detection of fibrosis in the advanced stages,and future developments promise to increase the reliability and accuracy of the staging of hepatic fibrosis.This article aims to describe the recent progress in the development of non-invasive assessment methods for the staging of liver fibrosis,with a special emphasize on computer-aided quantitative and deep learning methods.

Functional near-infrared spectroscopy in non-invasive neuromodulation

Non-invasive cerebral neuromodulation technologies are essential for the reorganization of cerebral neural networks,which have been widely applied in the field of central neurological diseases,such as stroke,Parkinson’s disease,and mental disorders.Although significant advances have been made in neuromodulation technologies,the identification of optimal neurostimulation paramete rs including the co rtical target,duration,and inhibition or excitation pattern is still limited due to the lack of guidance for neural circuits.Moreove r,the neural mechanism unde rlying neuromodulation for improved behavioral performance remains poorly understood.Recently,advancements in neuroimaging have provided insight into neuromodulation techniques.Functional near-infrared spectroscopy,as a novel non-invasive optical brain imaging method,can detect brain activity by measuring cerebral hemodynamics with the advantages of portability,high motion tole rance,and anti-electromagnetic interference.Coupling functional near-infra red spectroscopy with neuromodulation technologies offe rs an opportunity to monitor the cortical response,provide realtime feedbac k,and establish a closed-loop strategy integrating evaluation,feedbac k,and intervention for neurostimulation,which provides a theoretical basis for development of individualized precise neuro rehabilitation.We aimed to summarize the advantages of functional near-infra red spectroscopy and provide an ove rview of the current research on functional near-infrared spectroscopy in transcranial magnetic stimulation,transcranial electrical stimulation,neurofeedback,and braincomputer interfaces.Furthermore,the future perspectives and directions for the application of functional near-infrared spectroscopy in neuromodulation are summarized.In conclusion,functional near-infrared spectroscopy combined with neuromodulation may promote the optimization of central pellral reorganization to achieve better functional recovery form central nervous system diseases.

FibroScan-aspartate transaminase:A superior non-invasive model for diagnosing high-risk metabolic dysfunction-associated steatohepatitis

BACKGROUND Non-alcoholic fatty liver disease(NAFLD)with hepatic histological NAFLD activity score≥4 and fibrosis stage F≥2 is regarded as“at risk”non-alcoholic steatohepatitis(NASH).Based on an international consensus,NAFLD and NASH were renamed as metabolic dysfunction-associated steatotic liver disease(MASLD)and metabolic dysfunction-associated steatohepatitis(MASH),respectively;hence,we introduced the term“high-risk MASH”.Diagnostic values of seven non-invasive models,including FibroScan-aspartate transaminase(FAST),fibrosis-4(FIB-4),aspartate transaminase to platelet ratio index(APRI),etc.for high-risk MASH have rarely been studied and compared in MASLD.AIM To assess the clinical value of seven non-invasive models as alternatives to liver biopsy for diagnosing high-risk MASH.METHODS A retrospective analysis was conducted on 309 patients diagnosed with NAFLD via liver biopsy at Beijing Ditan Hospital,between January 2012 and December 2020.After screening for MASLD and the exclusion criteria,279 patients wereincluded and categorized into high-risk and non-high-risk MASH groups.Utilizing threshold values of each model,sensitivity,specificity,positive predictive value(PPV),and negative predictive values(NPV),were calculated.Receiver operating characteristic curves were constructed to evaluate their diagnostic efficacy based on the area under the curve(AUROC).RESULTS MASLD diagnostic criteria were met by 99.4%patients with NAFLD.The MASLD population was analyzed in two cohorts:Overall population(279 patients)and the subgroup(117 patients)who underwent liver transient elastography(FibroScan).In the overall population,FIB-4 showed better diagnostic efficacy and higher PPV,with sensitivity,specificity,PPV,NPV,and AUROC of 26.9%,95.2%,73.5%,72.2%,and 0.75.APRI,Forns index,and aspartate transaminase to alanine transaminase ratio(ARR)showed moderate diagnostic efficacy,whereas S index and gamma-glutamyl transpeptidase to platelet ratio(GPR)were relatively weaker.In the subgroup,FAST had the highest diagnostic efficacy,its sensitivity,specificity,PPV,NPV,and AUROC were 44.2%,92.3%,82.1%,67.4%,and 0.82.The FIB-4 AUROC was 0.76.S index and GPR exhibited almost no diagnostic value for high-risk MASH.CONCLUSION FAST and FIB-4 could replace liver biopsy as more effectively diagnostic methods for high-risk MASH compared to APRI,Forns index,ARR,S index,and GPR;FAST is superior to FIB-4.

A Study on Near-Infrared Non-Invasive Blood Glucose Concentration Regression Prediction Based on PSO-MKL-SVR

To improve the accuracy of predicting non-invasive blood glucose concentration in the near-infrared spectrum, we utilized the Particle Swarm Optimization (PSO) algorithm to optimize hyperparameters for the Multi-Kernel Learning Support Vector Machine (MKL-SVR). With these optimized hyperparameters, we established a non-invasive blood glucose regression model, referred to as the PSO-MKL-SVR model. Subsequently, we conducted a comparative analysis between the PSO-MKL-SVR model and the PSO-SVR model. In a dataset comprising ten volunteers, the PSO-MKL-SVR model exhibited significant precision improvements, including a 16.03% reduction in Mean Square Error and a 0.29% increase in the Squared Correlation Coefficient. Moreover, there was a 0.14% higher probability of the Clark’s Error Grid Analysis falling within Zone A. Additionally, the PSO-MKL-SVR model demonstrated a faster operational speed compared to the PSO-SVR model.

Observation on the Effect of Non-Invasive Ventilator Combined with Conventional Therapy in the Treatment of Chronic Obstructive Pulmonary Disease Complicated with Respiratory Failure

Objective:To explore the clinical effect of a non-invasive ventilator combined with conventional therapy in the treatment of patients with chronic obstructive pulmonary disease(COPD)combined with respiratory failure.Methods:68 patients with COPD combined with respiratory failure treated in our hospital from September 2021 to October 2023 were selected as the research subjects.Using the random number table method,they were divided into a control group and an experimental group of 34 cases each.The control group received conventional symptomatic treatment,and the experimental group received non-invasive ventilator treatment based on the control group.The clinical effects,blood gas indicators(partial pressure of carbon dioxide(PaCO_(2)),partial pressure of oxygen(PaO_(2)),arterial oxygen saturation(SaO_(2))),lung function(forced expiratory volume in 1 second(FEV1),forced vital capacity(FVC),6 min walking distance),complications,and inflammatory factor levels(c-reactive protein(CRP),interleukin-6(IL-6),neutrophil-to-lymphocyte ratio(NLR))of the two groups of patients were observed.Results:(1)The clinical efficacy of the patients in the experimental group(33/97.06%)was more significant as compared with the control group(25/73.53%)(P<0.05);(2)After treatment,the clinical efficacy of the two groups of patients in terms of FEV1,FEV1/FVC,6-minute walking distance,PaO_(2)and SaO_(2)all increased in the experimental group as compared to that of the control group(P<0.05);(3)After treatment,the PaCO_(2),CRP,IL-6,and NLR of the two groups of patients decreased,and the decrease in the experimental group was higher than that of the control group(P<0.05);(4)The patients’complication rate in the experimental group(2/5.88%)was lower as compared to that of the control group(9/26.46%)(P<0.05).Conclusion:Non-invasive ventilators combined with conventional therapy achieved good clinical results in treating patients with COPD and respiratory failure.

Analysis of the Effect of Non-Invasive Positive Pressure Ventilation in Emergency Treatment of Severe Bronchial Asthma with Respiratory Failure

Objective:This study aims to evaluate the clinical efficacy of non-invasive positive pressure ventilation(NIPPV)in patients with severe bronchial asthma combined with respiratory failure.Methods:90 patients with severe bronchial asthma combined with respiratory failure between September 2022 and December 2023 were selected for the study and randomly divided into the experimental group(NIPPV-assisted treatment)and the control group.The differences between the two groups were compared in terms of total effective rate of treatment,days of clinical symptom disappearance,days of hospitalization,lung function indexes,incidence of adverse reactions,and quality of life.Results:Patients in the experimental group had a significantly higher total effective rate of treatment(97.78%)than the control group(75.56%).In terms of pulmonary function indexes,patients in the experimental group showed significant improvement after treatment,especially the increase in forced expiratory volume and forced vital capacity,while these improvements were not as obvious in the control group.In addition,the incidence of adverse reactions was significantly lower in the experimental group than in the control group,suggesting that the application of NIPPV is relatively safe.Quality of life assessment also showed that patients in the experimental group had significantly better quality of life than the control group after treatment.Conclusion:This study demonstrated the effectiveness of NIPPV as an adjunctive treatment for severe bronchial asthma combined with respiratory failure.NIPPV can improve lung function,reduce the incidence of adverse effects,increase the overall effectiveness of the treatment,and contribute to the improvement of patients'quality of life.Therefore,NIPPV should be regarded as an effective and safe treatment in clinical management,especially in patients with severe bronchial asthma combined with respiratory failure,where its application has potential clinical significance.

Relationship Between Gene-Phenotype and Clinical Manifestations of Chromosomal Copy Number Variations Indicated by Non-Invasive Prenatal Testing

Objective:To analyze the clinical value of non-invasive prenatal testing(NIPT)in detecting chromosomal copy number variations(CNVs)and to explore the relationship between gene expression and clinical manifestations of chromosomal copy number variations.Methods:3551 naturally conceived singleton pregnant women who underwent NIPT were included in this study.The NIPT revealed abnormalities other than sex chromosome abnormalities and trisomy 13,18,and 21.Pregnant women with chromosome copy number variations underwent genetic counseling and prenatal ultrasound examination.Interventional prenatal diagnosis and chromosome microarray analysis(CMA)were performed.The clinical phenotypes and pregnancy outcomes of different prenatal diagnoses were analyzed.Additionally,a follow-up was conducted by telephone to track fetal development after birth,at six months,and one year post-birth.Results:A total of 53 cases among 3551 cases showed chromosomal copy number variation.Interventional prenatal diagnosis was performed in 36 cases:27 cases were negative and 8 were consistent with the NIPT test results.This indicates that NIPT’s positive predictive value(PPV)in CNVs is 22.22%.Conclusion:NIPT has certain clinical significance in screening chromosome copy number variations and is expected to become a routine screening for chromosomal microdeletions and microduplications.However,further interventional prenatal diagnosis is still needed to identify fetal CNVs.

Emerging role of non-invasive and liquid biopsy biomarkers in pancreatic cancer

A global increase in the incidence of pancreatic cancer(PanCa)presents a major concern and health burden.The traditional tissue-based diagnostic techniques provided a major way forward for molecular diagnostics;however,they face limitations based on diagnosis-associated difficulties and concerns surrounding tissue availability in the clinical setting.Late disease development with asymptomatic behavior is a drawback in the case of existing diagnostic procedures.The capability of cell free markers in discriminating PanCa from autoimmune pancreatitis and chronic pancreatitis along with other precancerous lesions can be a boon to clinicians.Early-stage diagnosis of PanCa can be achieved only if these biomarkers specifically discriminate the non-carcinogenic disease stage from malignancy with respect to tumor stages.In this review,we comprehensively described the non-invasive disease detection approaches and why these approaches are gaining popularity for their early-stage diagnostic capability and associated clinical feasibility.

Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness

BACKGROUND Acute bleeding due to esophageal varices(EVs)is a life-threatening complication in patients with cirrhosis.The diagnosis of EVs is mainly through upper gastrointestinal endoscopy,but the discomfort,contraindications and complications of gastrointestinal endoscopic screening reduce patient compliance.According to the bleeding risk of EVs,the Baveno VI consensus divides varices into high bleeding risk EVs(HEVs)and low bleeding risk EVs(LEVs).We sought to identify a non-invasive prediction model based on spleen stiffness measurement(SSM)and liver stiffness measurement(LSM)as an alternative to EVs screening.AIM To develop a safe,simple and non-invasive model to predict HEVs in patients with viral cirrhosis and identify patients who can be exempted from upper gastrointestinal endoscopy.METHODS Data from 200 patients with viral cirrhosis were included in this study,with 140 patients as the modelling group and 60 patients as the external validation group,and the EVs types of patients were determined by upper gastrointestinal endoscopy and the Baveno Ⅵ consensus.Those patients were divided into the HEVs group(66 patients)and the LEVs group(74 patients).The effect of each parameter on HEVs was analyzed by univariate and multivariate analyses,and a noninvasive prediction model was established.Finally,the discrimination ability,calibration ability and clinical efficacy of the new model were verified in the modelling group and the external validation group.RESULTS Univariate and multivariate analyses showed that SSM and LSM were associated with the occurrence of HEVs in patients with viral cirrhosis.On this basis,logistic regression analysis was used to construct a prediction model:Ln[P/(1-P)]=-8.184-0.228×SSM+0.642×LSM.The area under the curve of the new model was 0.965.When the cut-off value was 0.27,the sensitivity,specificity,positive predictive value and negative predictive value of the model for predicting HEVs were 100.00%,82.43%,83.52%,and 100%,respectively.Compared with the four prediction models of liver stiffness-spleen diameter to platelet ratio score,variceal risk index,aspartate aminotransferase to alanine aminotransferase ratio,and Baveno VI,the established model can better predict HEVs in patients with viral cirrhosis.CONCLUSION Based on the SSM and LSM measured by transient elastography,we established a non-invasive prediction model for HEVs.The new model is reliable in predicting HEVs and can be used as an alternative to routine upper gastrointestinal endoscopy screening,which is helpful for clinical decision making.

Non-invasive detection of pancreatic cancer by measuring DNA methylation of Basonuclin 1 and Septin 9 in plasma

Pancreatic cancer (PC), a deadly malignancy with an overall 5-year survival rate of 5% to 15%, is ranked as the seventh leading cause of cancer death in the world in spite of its low occurrence rate.[1,2] Early detection appears to be the most effective approach to improve the overall survival of patients with PC. However, the difficulty in early detection of PC is a lack of specific symptoms and reliable biomarkers. Currently, carbohydrate antigen 19-9 (CA 19-9) is a serum biomarker that is widely used in PC detection. However, 10% of patients with PC cannot produce CA 19-9 and serum CA 19-9 is frequently absent in patients with early-stage cancer. Furthermore, CA 19-9 is often found to be elevated in benign conditions or in other cancers, making its utility limited. Therefore, it is important to identify new diagnostic biomarkers to improve PC detection.

Biomarkers for detecting colorectal cancer non-invasively: DNA,RNA or proteins?

Colorectal cancer(CRC)is a global problem affecting millions of people worldwide.This disease is unique because of its slow progress that makes it preventable and often curable.CRC symptoms usually emerge only at advanced stages of the disease,consequently its early detection can be achieved only through active population screening,which markedly reduces mortality due to this cancer.CRC screening tests that employ non-invasively detectable biomarkers are currently being actively developed and,in most cases,samples of either stool or blood are used.However,alternative biological substances that can be collected non-invasively(colorectal mucus,urine,saliva,exhaled air)have now emerged as new sources of diagnostic biomarkers.The main categories of currently explored CRC biomarkers are:(1)Proteins(comprising widely used haemoglobin);(2)DNA(including mutations and methylation markers);(3)RNA(in particular microRNAs);(4)Low molecular weight metabolites(comprising volatile organic compounds)detectable by metabolomic techniques;and(5)Shifts in gut microbiome composition.Numerous tests for early CRC detection employing such non-invasive biomarkers have been proposed and clinically studied.While some of these studies generated promising early results,very few of the proposed tests have been transformed into clinically validated diagnostic/screening techniques.Such DNA-based tests as Food and Drug Administration-approved multitarget stool test(marketed as Cologuard®)or blood test for methylated septin 9(marketed as Epi proColon®2.0 CE)show good diagnostic performance but remain too expensive and technically complex to become effective CRC screening tools.It can be concluded that,despite its deficiencies,the protein(haemoglobin)detection-based faecal immunochemical test(FIT)today presents the most cost-effective option for non-invasive CRC screening.The combination of non-invasive FIT and confirmatory invasive colonoscopy is the current strategy of choice for CRC screening.However,continuing intense research in the area promises the emergence of new superior non-invasive CRC screening tests that will allow the development of improved disease prevention strategies.

Non-Invasive Approach to Early Diagnosis of the Formation of Oncological Neoplasms

The currently developed instrumental approaches for detecting pathological changes in the body have a number of disadvantages. The most important of them is that the equipment is sensitive to the detection of diseases only from a certain threshold level of destructive changes in the body. The present article discusses the possibility of using the new instrumental complex “Bioscope” for early and non-invasive diagnosis of the beginning of the formation of ontological neoplasm’s in the body.

Invasive versus non-invasive ventilation in patients with COVID-19 pneumonia:A retrospective study

Objective:To compare the survival and length of stay of invasive ventilation(IV)with those of non-invasive ventilation(NIV)in patients with COVID-19 acute respiratory distress syndrome in a single hospital from May 2020 to March 2021.Methods:After obtaining approval from the Hospital Director,the data of COVID-19 patients including demographics,type of respiratory support(non-invasive ventilation or invasive ventilation),duration of ventilation,length of stay,discharge,and death were collected and analyzed.Results:Out of the 152 patients identified,134 patients were analyzed.The median intubation days were 10.0(Q1:3.5,Q3:13.5)in the IV group and 0.0(Q1:0.0,Q3:0.0)days in the NIV-only group.Out of the 101 patients who received NIV,43 patients were subsequently intubated due to failure of NIV.Of the 63 patients(47.01%)who died,22(66.66%)were from the IV group and 40(92.02%)were from the NIV-followed-by-intubation group,and 1(1.72%)were from the NIV-only group.Multivariate analysis showed that the presence of a respiratory comorbidity(OR=16.56,95%CI=1.56-175.48,P=0.02)was an independent predictor of survival.Conclusions:Respiratory co-morbidity is a significant adverse predictor of survival outcome.The decision on the type of respiratory support should be made on a patient-to-patient basis.

Real-time Rescue Target Detection Based on UAV Imagery for Flood Emergency Response

Timely acquisition of rescue target information is critical for emergency response after a flood disaster.Unmanned Aerial Vehicles(UAVs)equipped with remote sensing capabilities offer distinct advantages,including high-resolution imagery and exceptional mobility,making them well suited for monitoring flood extent and identifying rescue targets during floods.However,there are some challenges in interpreting rescue information in real time from flood images captured by UAVs,such as the complexity of the scenarios of UAV images,the lack of flood rescue target detection datasets and the limited real-time processing capabilities of the airborne on-board platform.Thus,we propose a real-time rescue target detection method for UAVs that is capable of efficiently delineating flood extent and identifying rescue targets(i.e.,pedestrians and vehicles trapped by floods).The proposed method achieves real-time rescue information extraction for UAV platforms by lightweight processing and fusion of flood extent extraction model and target detection model.The flood inundation range is extracted by the proposed method in real time and detects targets such as people and vehicles to be rescued based on this layer.Our experimental results demonstrate that the Intersection over Union(IoU)for flood water extraction reaches an impressive 80%,and the IoU for real-time flood water extraction stands at a commendable 76.4%.The information on flood stricken targets extracted by this method in real time can be used for flood emergency rescue.

Automatic detection of small bowel lesions with different bleeding risks based on deep learning models

BACKGROUND Deep learning provides an efficient automatic image recognition method for small bowel(SB)capsule endoscopy(CE)that can assist physicians in diagnosis.However,the existing deep learning models present some unresolved challenges.AIM To propose a novel and effective classification and detection model to automatically identify various SB lesions and their bleeding risks,and label the lesions accurately so as to enhance the diagnostic efficiency of physicians and the ability to identify high-risk bleeding groups.METHODS The proposed model represents a two-stage method that combined image classification with object detection.First,we utilized the improved ResNet-50 classification model to classify endoscopic images into SB lesion images,normal SB mucosa images,and invalid images.Then,the improved YOLO-V5 detection model was utilized to detect the type of lesion and its risk of bleeding,and the location of the lesion was marked.We constructed training and testing sets and compared model-assisted reading with physician reading.RESULTS The accuracy of the model constructed in this study reached 98.96%,which was higher than the accuracy of other systems using only a single module.The sensitivity,specificity,and accuracy of the model-assisted reading detection of all images were 99.17%,99.92%,and 99.86%,which were significantly higher than those of the endoscopists’diagnoses.The image processing time of the model was 48 ms/image,and the image processing time of the physicians was 0.40±0.24 s/image(P<0.001).CONCLUSION The deep learning model of image classification combined with object detection exhibits a satisfactory diagnostic effect on a variety of SB lesions and their bleeding risks in CE images,which enhances the diagnostic efficiency of physicians and improves the ability of physicians to identify high-risk bleeding groups.

Letter to editor‘Non-invasive model for predicting high-risk esophageal varices based on liver and spleen stiffness’

predicting high-risk esophageal varices based on liver and spleen stiffness".Acute bleeding caused by esophageal varices is a life-threatening complication in patients with liver cirrhosis.Due to the discomfort,contraindications,and associated complications of upper gastrointestinal endoscopy screening,it is crucial to identify an imaging-based non-invasive model for predicting high-risk esophageal varices in patients with cirrhosis.

Evaluation of Non-Invasive Markers of Liver Fibrosis in Chronic Hepatitis B Patients in a Sub-Saharan African Setting: Transient Elastography versus APRI, FIB4, GTT/Platelet Scores

Background: Non-invasive markers which use routine laboratory tests are less expensive and highly needed to assess and stage liver fibrosis in chronic hepatitis B patients in Sub-Saharan Africa. We aimed at evaluating liver fibrosis, using the Aspartate aminotransferase to Platelet Ratio Index (APRI), Fibrosis Index Based on 4 factors (FIB4), and Gamma-glutamyl transpeptidase to Platelet Ratio (GPR) in chronic hepatitis B patients with transient elastography as the reference so as to choose an alternative to transient elastography. Method: We carried out a cross-sectional study using the records of patients who attended the Douala General Hospital and Marie O Polyclinic Douala from 2012 to 2017. Non-invasive tests were compared with Transient Elastography. The Spearman coefficient was used to determine correlation. The sensitivity, specificity, positive predictive values and negative predictive values were used to get the optimal cut-off values. The diagnostic accuracy was estimated by calculating the area under the Receiver Operating Characteristic Curve (ROC). P Results: Of the 243 patient records studied, the median age or interquartile range (IQR) was 35 (29 - 42) years with a male predominance of 73.7%. More than 60% of the study population had normal transaminases. Significant fibrosis was found in 88 (36.2%) patients and 32 (13.7%) patients had cirrhosis. APRI had the best cut-off values and highest area under the ROC Curve, for significant fibrosis and cirrhosis with 0.55 (0.823 95% CI [0.769 - 0.869], P Conclusion: APRI, had the best diagnostic properties to detect liver fibrosis and cirrhosis in patients with Chronic Hepatitis B in Douala. The cut-off values are 0.55 and 0.65 for significant fibrosis and cirrhosis respectively.

A dual-RPA based lateral flow strip for sensitive,on-site detection of CP4-EPSPS and Cry1Ab/Ac genes in genetically modified crops

Traditional transgenic detection methods require high test conditions and struggle to be both sensitive and efficient.In this study,a one-tube dual recombinase polymerase amplification(RPA)reaction system for CP4-EPSPS and Cry1Ab/Ac was proposed and combined with a lateral flow immunochromatographic assay,named“Dual-RPA-LFD”,to visualize the dual detection of genetically modified(GM)crops.In which,the herbicide tolerance gene CP4-EPSPS and the insect resistance gene Cry1Ab/Ac were selected as targets taking into account the current status of the most widespread application of insect resistance and herbicide tolerance traits and their stacked traits.Gradient diluted plasmids,transgenic standards,and actual samples were used as templates to conduct sensitivity,specificity,and practicality assays,respectively.The constructed method achieved the visual detection of plasmid at levels as low as 100 copies,demonstrating its high sensitivity.In addition,good applicability to transgenic samples was observed,with no cross-interference between two test lines and no influence from other genes.In conclusion,this strategy achieved the expected purpose of simultaneous detection of the two popular targets in GM crops within 20 min at 37°C in a rapid,equipmentfree field manner,providing a new alternative for rapid screening for transgenic assays in the field.