Screening Method Research Articles

Revolutionizing early breast cancer screening: Advanced multi-spectral transmission imaging classification with improved Otsu's method and K-means clustering

Breast cancer stands as a formidable danger to the health of women worldwide, underscoring the critical need for effective screening methods. Multispectral transmission imaging offers a promising avenue due to its non-invasive potential for early screening. Some researchers already suggested registration to solve the problem of jitters due to respiration and movement and frame accumulation technology to solve the low grayscale problem. However, the classification of blood vessels and breast tissue in breast images often suffers from low signal-to-noise ratio (SNR) and low contrast, hindering accurate classification. This paper proposes a novel improved Otsu's method with K-Means clustering to address this challenge. The proposed method aims to enhance the foundation for classification using multispectral transmission images. The study utilizes multispectral transmission images captured at four wavelengths, representing an innovative avenue for early, affordable breast cancer screening research. Initially, 300 images are registered and accumulated to prove the efficiency of the suggested methodology. Then, median filtering is applied to reduce noise in the images. Improved Otsu's segmentation method is then employed to separate blood vessels from breast tissue. After that, K-means clustering is utilized to accurately classify these components. The results of the proposed method demonstrate significant improvements in classification accuracy and grayscale contrast of multispectral breast images. By effectively distinguishing blood vessels and breast tissue, the proposed methodology addresses the inherent challenges of low contrast in multispectral transmission imaging. This advancement offers a clearer pathway for early breast cancer screening.

DART isotope dilution high resolution mass spectrometry and 19F-NMR detection of fluorotelomeric alcohols in hydrolyzed food contact paper

Fluorotelomer-based acrylate polymers and surfactants used to grease-proof food contact paper (FCP) are potential sources of dietary exposure to perfluoroalkyl substances (PFAS). Food contact substances (FCS) containing polyfluorinated long-chains (≥C8) were voluntarily removed by their manufacturers from the U.S. market in 2011 due to health concerns and largely replaced with FCSs containing short-chain (≤C7) PFAS. In 2020, FDA findings of potential biopersistence of 6:2 FTOH (CF3(CF2)5CH2CH2OH) similarly prompted an additional voluntarily phase-out of FCSs containing 6:2 FTOH by their manufacturers that was completed by the end of 2023. To monitor the phase-out process, a screening method was developed to detect FCPs containing ester-linked polyfluorinated pendant chains. Direct Analysis in Real Time-Isotope Dilution-High Resolution Mass Spectrometry (DART-ID-HRMS) enabled rapid semi-quantitative detection of 6:2 FTOH in FCP saponification reaction headspace without requiring sample concentration or chromatography. 19F-NMR analysis confirmed 6:2 FTOH pendant chain identity and detection dependence on saponification. The speed and specificity of this approach arise from ester saponification in the presence of stable isotopically labeled 6:2 FTOH; high FTOH differential volatility relative to nonfluorinated matrix, and the facile production of FTOH gas-phase anions (e.g., [M + O2]·−, [M-H + CO2]−) under ambient ionization conditions. The efficiency of this simple workflow makes it well-suited for monitoring the phase-out of FCS containing ester-linked polyfluorinated chains from the U.S. marketplace.

Risks associated with cancer screening programmes among multimorbid patients: a systematic review

Abstract Background Cancer screening programmes have been implemented to facilitate early detection of cancer. However, there are risks associated with cancer screening, such as overdiagnosis. This means identifying problems that were never going to cause harm1. This includes identification of abnormalities that do not progress, or that progress too slowly to cause symptoms or harm during a person’s remaining lifetime in the context of multi-morbidity1,2. Aim We conducted a systematic review of the literature to explore the harms associated with overdiagnosis in multimorbid patients when they undergo three different types of cancer screening programmes. Methods The search was conducted on MEDLINE, EMBASE, PSYCHINFO and Scopus from 1960 (cancer screening programmes implementation) until November 2023. Inclusion criteria involved studies with multimorbid participants (having two or more chronic conditions), having one of three common types of cancers (i.e., breast, prostate and lung), and used a standardised method for screening (i.e., mammography, Prostate-specific antigen test, and Low Dose Computed tomography (LDCT) or Computed Tomography scans (CT)). Only peer-reviewed studies published in English were included. Four keyword sets were used, “Multimorbidity”, “Overdiagnosis “, “Patient harms” and “Cancer screening”. Two independent reviewers conducted the search and data extraction. Rayyan web application was used to help with title, and abstract screening, and to compare the independent reviews. The Newcastle-Ottawa scale was used for quality assessment. This systematic review was registered with PROSPERO database (CRD42024475175) and followed the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) guidance. Ethical approval was not required to undertake this review. Results A total of 200 studies resulted from all the databases search and duplicates (n=29) removed. Titles, abstracts and full-texts were screened, with seven studies meeting the inclusion criteria. Quality assessment of the included studies showed two studies of good quality and five studies of poor quality. All included studies were conducted in the United States. Breast cancer overdiagnosis increased with increasing the number of comorbidities. Rates of overdiagnosis with prostate cancer were higher compared to breast cancer, with multimorbid patients having a 15% higher risk of overdiagnosed malignancies, compared to non-multimorbid individuals. Harms of overdiagnosis were categorised into psychological (e.g. anxiety), physical (e.g. side effects of medications) and financial (e.g. costs to healthcare systems). Overdiagnosis with lung cancer was associated with increased anxiety, with more individuals dying from other causes than lung cancer in post-mortem studies, questioning the risk versus benefit of lung cancer screening result interpretation for non-progressive disease. Conclusion The emergence of sophisticated testing technologies and greater access to screening tests can contribute to overdiagnosis. We found many different types of harm related to overdiagnosis in common types of cancer. Further research is required to explore the risk of overdiagnosis with other types of cancer. Awareness of clinicians about the risks of overdiagnosis, particularly in high-risk population, such as multimorbid patients, could guide their decision-making regarding non-progressive cancer treatment.

The Development of a Non-Invasive Screening Method Based on Serum microRNAs to Quantify the Percentage of Liver Steatosis

Metabolic dysfunction-associated steatotic liver disease (MASLD) is often asymptomatic and underdiagnosed; consequently, there is a demand for simple, non-invasive diagnostic tools. In this study, we developed a method to quantify liver steatosis based on miRNAs, present in liver and serum, that correlate with liver fat. The miRNAs were analyzed by miRNAseq in liver samples from two cohorts of patients with a precise quantification of liver steatosis. Common miRNAs showing correlation with liver steatosis were validated by RT-qPCR in paired liver and serum samples. Multivariate models were built using partial least squares (PLS) regression to predict the percentage of liver steatosis from serum miRNA levels. Leave-one-out cross validation and external validation were used for model selection and to estimate predictive performance. The miRNAseq results disclosed (a) 144 miRNAs correlating with triglycerides in a set of liver biobank samples (n = 20); and (b) 124 and 102 miRNAs correlating with steatosis by biopsy digital image and MRI analyses, respectively, in liver samples from morbidly obese patients (n = 24). However, only 35 miRNAs were common in both sets of samples. RT-qPCR allowed to validate the correlation of 10 miRNAs in paired liver and serum samples. The development of PLS models to quantitatively predict steatosis demonstrated that the combination of serum miR-145-3p, 122-5p, 143-3p, 500a-5p, and 182-5p provided the lowest root mean square error of cross validation (RMSECV = 1.1, p-value = 0.005). External validation of this model with a cohort of mixed MASLD patients (n = 25) showed a root mean squared error of prediction (RMSEP) of 5.3. In conclusion, it is possible to predict the percentage of hepatic steatosis with a low error rate by quantifying the serum level of five miRNAs using a cost-effective and easy-to-implement RT-qPCR method.

Prevalence and screening of hemoglobinopathies and glucose-6-phosphate dehydrogenase deficiency in Yemeni blood donors

ABSTRACT Hemoglobinopathies and Glucose-6-Phosphate Dehydrogenase (G6PD) deficiency pose significant health threats in Yemen, which can be alleviated through robust preventive strategies, highlighting the importance of implementing a cost-effective and efficient blood donor screening method to facilitate early diagnosis and management of erythrocyte disorders, ultimately improving both donor safety and patient health outcomes. Objectives This study aimed to determine the prevalence of total blood cell abnormalities, hemoglobinopathies and G6PD deficiency and evaluate the efficacy of red blood cell (RBC) indices, mentzer index (MI) and naked-eye single tube red cell osmotic fragility (NESTROF) test as screening tools for diagnosis of β thalassemia trait among Yemeni blood donors. Methods A cross-sectional study was conducted with 106 volunteer blood donors who met the national standard criterion of blood donation. Various tests were performed, including complete blood count (CBC), serum ferritin, sickling test, G6PD assay, NESTROF test and high-performance liquid chromatography (HPLC). Results The prevalence of hematological abnormalities among blood donors reached 68.9%, with functional RBC abnormalities at 51.9%, leukopenia at 10.4%, thrombocytosis at 1.9%, and thrombocytopenia at 4.7%. Additionally, hemoglobinopathies were found in 21.7% of donors, with β-thalassemia trait at 3.8%, sickle cell trait at 1.9%, and suspected α-thalassemia trait at 16%, while G6PD deficiency and iron deficiency were present in 12.3% and 17.9% of donors, respectively. The NESTROF test, MCV and MCH demonstrated a sensitivity rate of 100%. MI and MCH exhibited the highest specificity followed by NESTROF test in the screening of β-thalassemia trait. Conclusions The prevalence of hemoglobinopathies and G6PD deficiency appear to be common among Yemeni blood donors. These results emphasize the necessity of comprehensive blood donation screening programs to safeguard the blood supply and promote early detection and management of hemoglobinopathies and G6PD deficiency in Yemen.

Modeling Drug Responses and Evolutionary Dynamics using Patient-Derived Xenografts Reveals Precision Medicine Strategies for Triple Negative Breast Cancer.

The inter- and intra-tumor heterogeneity of triple negative breast cancers (TNBC), which is reflected in diverse drug responses, interplays with tumor evolution. Here, we developed a preclinical experimental and analytical framework using treatment-naive TNBC patient-derived tumor xenografts (PDTX) to test their predictive value in personalized cancer treatment approaches. Patients and their matched PDTX exhibited concordant drug responses to neoadjuvant therapy using two trial designs and dosing schedules. This platform enabled analysis of non-genetic mechanisms involved in relapse dynamics. Treatment resulted in permanent phenotypic changes with functional and therapeutic consequences. High throughput drug screening methods in ex vivo patient derived tumor xenograft cells (PDTCs) revealed patient-specific drug response changes dependent on first-line therapy. This was validated in vivo, as exemplified by a change in olaparib sensitivity in tumors previously treated with clinically relevant cycles of standard-of-care chemotherapy. In summary, PDTXs provide a robust tool to test patient drug responses and therapeutic regimens and to model evolutionary trajectories. However, high inter-model variability and permanent non-genomic transcriptional changes constrain their use for personalized cancer therapy. This work highlights important considerations associated with preclinical drug response modeling and potential uses of the platform to identify efficacious and preferential sequential therapeutic regimens.

Adopting Non-invasive Approaches into Precision Colorectal Cancer Screening.

Effective screening is essential to reducing CRC incidence and mortality by detecting the disease at early stages and identifying non-invasive precursors. While colonoscopy remains the most sensitive modality to visualize and remove neoplastic lesions thereby reducing CRC and the related death, its high cost and invasive nature limit its widespread use. The fecal immunochemical test (FIT), which offers a non-invasive alternative with higher public acceptance and comparable cost-effectiveness to colonoscopy, has become the preferred screening method in many regions. Newer non-invasive tests, such as multitarget stool DNA or RNA tests, have shown improved sensitivity for CRC and advanced adenomas, although their high costs and lower specificity present challenges for large-scale implementation. Blood-based circulating cell-free DNA test also offer promise but still require optimization to be cost-effective. The heterogeneity of the screening population further complicates the effectiveness of CRC screening programs. Variations in non-communicable disease risk factors, such as metabolic syndrome, lifestyle habits, and comorbidities, can significantly influence CRC risk and screening outcomes. Moreover, diverse screening behaviors, including inconsistent adherence to recommended screening intervals and the interchangeable use of different screening modalities, add complexity to achieving uniform effectiveness across populations. This variability underscores the need for personalized screening strategies that consider individual risk profiles and screening behaviors, as well as the application of cutting-edge technologies such as big data analytics, artificial intelligence, and digital twin approaches to evaluate its effectiveness. This article reviews the current CRC screening strategies, the advantages of non-invasive methods, and the potential of fecal hemoglobin concentration, to tailor screening intervals and improve risk stratification. It also discusses the emerging role of real-world data and advanced technologies in enhancing CRC screening accuracy and effectiveness, particularly in complex real-world scenarios where traditional methods may fall short. Before novel non-invasive approaches, such as ctDNA tests or polygenic risk scores, are validated and proven cost-effective, exploring the clinical utility of FIT and its quantitative measurement in both screening and surveillance by integrating real-world clinical big data seems a feasible direction for achieving sustained development in population screening.

High-Throughput Discovery of Substrate Peptide Sequences for E3 Ubiquitin Ligases Using a cDNA Display Method.

Cells utilize ubiquitin as a posttranslational protein modifier to convey various signals such as proteasomal degradation. The disfunction of ubiquitylation or following proteasomal degradation can give rise to the accumulation and aggregation of improperly ubquitylated proteins, which is known to be a general causation of many neurodegenerative diseases. Thus, the characterization of substrate peptide sequences of E3 ligases is crucial in biological and pharmaceutical sciences. In this study, we developed a novel high-throughput screening system for substrate peptide sequences of E3 ligases using a cDNA display method, which enables covalent conjugation between peptide sequences and their corresponding cDNA sequences. First, we focused on the MDM2 E3 ligase and its known peptide substrate as a model to establish the screening method, and confirmed that cDNA display method was compatible with in vitro ubiquitylation. Then, we demonstrated identification of MDM2 substrate sequences from random libraries to identify a novel motif (VKFTGGQLA). Bioinformatics analysis of the hit sequences was performed to gain insight about endogenous substrate proteins.

Assessment of muscle strength in elderly as a screening method for sarcopenia in primary care: a scoping review

ObjectivesTo identify and map the available evidence for whether a test of handgrip strength (HGS) and/or the chair stand test (CST) have been used as screening tools for the detection...

Self-testing for human papillomavirus as a screening method for identifying risk groups

Due to the high prevalence of cervical cancer, it is necessary to take measures aimed at reducing its frequency through vaccination, screening, detection and treatment of precancerous conditions. The article presents a systematic analysis of scientific data on the use of testing for self-sampling for human papillomavirus as a tool to improve the effectiveness of screening and detection of precancerous diseases of the cervix. It has been shown that the use of such tests, which are based on polymerase chain reaction (PCR), have similar clinical accuracy compared to sampling by a doctor, and thus this option is promising for expanding the coverage of cervical cancer screening. The presence of expected economic efficiency also determines the relevance and prospects for these tests, but further research is needed to assess their implementation in routine practice.

Higher detectability of amyloid with phenol Congo red compared with alkaline Congo red

IntroductionAmyloidosis is a heterogeneous group of conditions associated with tissue deposition of insoluble abnormal proteins that damage vital organs. Early diagnosis, when the deposits are minimal, determines the prognosis and requires histological confirmation. The commonly adopted gold standard technique is alkaline Congo red (ACR) staining, though its sensitivity is limited. There is a need for a simple and inexpensive screening method offering a better chance of detecting mini­mal amyloid deposits. The aim of this study was to compare amyloid detectability with ACR and phenol Congo red (PHCR) staining techniques for early detection of minimal deposits.Material and methodsWe assessed 452 tissue specimens (including adipose tissue, gastrointestinal mucosa, labial salivary gland, myocardium, and bone marrow) from 425 patients with clinically suspected systemic or local amyloidosis, which had been sent to the Pathology Laboratory of the National Institute of Geriatrics, Rheumatology and Rehabilitation in Warsaw. Adjacent sections from each specimen were stained with ACR and PHCR. If amyloid was detected, immunohistochemical typing was conducted. The consistency of the two staining methods was expressed as Cohen’s κ coefficient.ResultsA total of 169 tissue specimens (37%) yielded positive readings, with 93 cases ACR(+) and PHCR(+); 75 cases ACR(–) and PHCR(+), and 1 case ACR(+) and PHCR(–). The percentage agreement between the staining methods was 83%, with the Cohen’s κ coefficient value of 0.60 (95% CI: 0.52–0.69), which corresponds to moderate agreement according to Fleiss. Additional immunohistochemical amyloid typing, conducted in ACR(–) and PHCR(+) specimens, yielded conclusive results in 82% of cases.ConclusionsThe use of PHCR staining as a screening method in suspected amyloidosis improves amyloid (light chain, transthyretin, and amyloid A protein) detectability in various tissues. The PHCR staining specificity should be verified via electron microscopy and/or mass spectrometry.

Detection of equine parvovirus-hepatitis and efficacy of governmental regulation for equine biologics purity.

In 2018, a new virus, named equine parvovirus-hepatitis (EqPV-H), was discovered in a biologic product that had been administered to horses that subsequently developed clinical signs of equine serum hepatitis (Theiler disease). Further correlation of the virus with the disease sparked federal requirements that all equine biologics be free of EqPV-H. The initial quantitative real-time PCR (qPCR) test for EqPV-H has proved to be sensitive to co-extracted PCR inhibitors in template nucleic acids, causing false-negative results. We investigated the use of digital PCR (dPCR) as a more robust test. Examination of 227 equine biologic product lots available for purchase both before and after regulatory implementation using both detection methods indicated that dPCR is a more reliable platform. Nevertheless, use of the qPCR method for product screening had reduced the fraction of serials with EqPV-H detected from 39.6% prior to regulation to 6.8% after regulatory implementation. Adoption of dPCR testing is an opportunity to further decrease the prevalence of EqPV-H in equine biologics.

Editorial Comment: An Alternate Method for Primary Breast Cancer Screening in Low-Resource Settings.

Editorial Comment: An Alternate Method for Primary Breast Cancer Screening in Low-Resource Settings.

Folate Receptor Alpha—A Secret Weapon in Ovarian Cancer Treatment?

Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy worldwide. Due to its nonspecific symptoms and unreliable screening tools, EOC is not diagnosed at an early stage in most cases. Unfortunately, despite achieving initial remission after debulking surgery and platinum-based chemotherapy, most patients experience the recurrence of the disease. The limited therapy approaches have encouraged scientists to search for new detection and therapeutic strategies. In this review, we discuss the role of folate receptor alpha (FRα) in EOC development and its potential application as a biomarker and molecular target in designing new EOC screening and treatment methods. We summarize the mechanisms of the action of various therapeutic strategies based on FRα, including MABs (monoclonal antibodies), ADCs (antibody–drug conjugates), FDCs (folate–drug conjugates), SMDCs (small molecule–drug conjugates), vaccines, and CAR-T (chimeric antigen receptor T) cells, and present the most significant clinical trials of some FRα-based drugs. Furthermore, we discuss the pros and cons of different FR-based therapies, highlighting mirvetuximab soravtansine (MIRV) as the currently most promising EOC-targeting drug.

Recursive-RARE-based three-dimensional parameter estimation of near-field source considering amplitude attenuation

This paper addresses the issue for near-field (NF) localization considering amplitude attenuation, proposing a recursive rank-reduction (RARE) method for three-dimensional (3-D) parameter estimation of NF sources incident on a symmetrical cross array. The proposed method constructs several one-dimensional (1-D) spectral peak search estimators to obtain two-dimensional angle and range parameters. Initially, using the received data from symmetrical array elements in one axis, a 1-D spectral peak search estimator is constructed. The origins of two types of pseudo peaks within this estimator are analyzed, and then, corresponding pseudo peaks removal methods, namely the initial screening method and the recursive RARE method, are presented to obtain the estimate of the first angle parameter. Subsequently, the estimated results are fed into another 1-D spectral peak search estimator constructed from the original received data to obtain the range parameter. Finally, the same process is applied to the other axis to obtain the second angle and range parameters, followed by a parameter matching operation for 3-D parameters. Compared to existing NF source localization methods, the proposed method more effectively eliminates pseudo peaks, and demonstrates superior parameter estimation performance under conditions of small number of snapshots and low signal-to-noise ratio, as validated by several simulation results.

AI‐Enhanced Gait Analysis Insole with Self‐Powered Triboelectric Sensors for Flatfoot Condition Detection

AbstractFlatfoot is an orthopedic malformation where the inner foot arch flattens during motion, potentially leading to chronic musculoskeletal issues. Monitoring foot conditions is essential, as existing screening methods often need more objectivity and cost‐effectiveness. This research develops an insole‐based screening device using self‐powered triboelectric nanogenerators (TENGs) as tactile sensors and Arduino hardware setup. TENG converts mechanical energy into electrical energy, offering simple fabrication, cost‐effectiveness, longevity, and high‐output power benefits. The device records the electrical output generated by foot movements via Arduino and sends data via Bluetooth to the processing tool. Machine learning algorithms employing the Random Forest Classifier process the data to detect flatfoot conditions accurately after training sessions. For data collection, 100 participants are asked to march and walk for the same duration and distance, ensuring consistent output. Analysis reveals that the insoles' middle sensors produce higher electricity levels in individuals with flatfoot, showing a uniform pressure distribution across the foot and contact in the arch area. In contrast, individuals with normal feet exert more pressure on the toe and heel foot areas. The system achieves an overall accuracy of 82%, demonstrating the insole's potential as a commercial flatfoot detection device.

Leveraging calcium score CT radiomics for heart failure risk prediction.

Studies have used extensive clinical information to predict time-to-heart failure (HF) in patients with and without diabetes mellitus (DM). We aimed to determine a screening method using only computed tomography calcium scoring (CTCS) to assess HF risk. We analyzed CTCS scans from 1,998 patients (336 with type 2 diabetes) from a no-charge coronary artery calcium score registry (CLARIFY Study, Clinicaltrials.gov NCT04075162). We used deep learning to segment epicardial adipose tissue (EAT) and engineered radiomic features of calcifications ("calcium-omics") and EAT ("fat-omics"). We developed models incorporating radiomics to predict risk of incident HF in patients with and without type 2 diabetes. At a median follow-up of 1.7 years, 5% had incident HF. In the overall cohort, fat-omics (C-index: 77.3) outperformed models using clinical factors, EAT volume, Agatston score, calcium-omics, and calcium-and-fat-omics to predict HF. For DM patients, the calcium-omics model (C-index: 81.8) outperformed other models. In conclusion, CTCS-based models combining calcium and fat-omics can predict incident HF, outperforming prediction scores based on clinical factors.Please check article title if captured correctly.YesPlease check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.Yes.

High‐Throughput Absorbance‐Activated Droplet Sorting for Engineering Aldehyde Dehydrogenases

AbstractRecent decades have seen a dramatic increase in the commercial use of biocatalysts, transitioning from energy‐intensive traditional chemistries to more sustainable methods. Current enzyme engineering techniques, such as directed evolution, require the generation and testing of large mutant libraries to identify optimized variants. Unfortunately, conventional screening methods are unable to screen such large libraries in a robust and timely manner. Droplet‐based microfluidic systems have emerged as a powerful high‐throughput tool for library screening at kilohertz rates. Unfortunately, almost all reported systems are based on fluorescence detection, restricting their use to a limited number of enzyme types that naturally convert fluorogenic substrates or require the use of surrogate substrates. To expand the range of enzymes amenable to evolution using droplet‐based microfluidic systems, we present an absorbance‐activated droplet sorter that allows droplet sorting at kilohertz rates without the need for optical monitoring of the microfluidic system. To demonstrate the utility of the sorter, we rapidly screen a 105‐member aldehyde dehydrogenase library towards D‐glyceraldehyde using a NADH mediated coupled assay that generates WST‐1 formazan as the colorimetric product. We successfully identify a variant with a 51 % improvement in catalytic efficiency and a significant increase in overall activity across a broad substrate spectrum.

Exploring the Features and Trends of Industrial Product E-Commerce in China Using Text-Mining Approaches

Industrial product e-commerce refers to the specific application of the e-commerce concept in industrial product transactions. It enables industrial enterprises to conduct transactions via Internet platforms and reduce circulation and operating costs. Industrial literature, such as policies, reports, and standards related to industrial product e-commerce, contains much crucial information. Through a systematical analysis of this information, we can explore and comprehend the development characteristics and trends of industrial product e-commerce. To this end, 18 policy documents, 10 industrial reports, and five standards are analyzed by employing text-mining methods. Firstly, natural language processing (NLP) technology is utilized to pre-process the text data related to industrial product commerce. Then, word frequency statistics and TF-IDF keyword extraction are performed, and the word frequency statistics are visually represented. Subsequently, the feature set is obtained by combining these processes with the manual screening method. The original text corpus is used as the training set by employing the skip-gram model in Word2Vec, and the feature words are transformed into word vectors in the multi-dimensional space. The K-means algorithm is used to cluster the feature words into groups. The latent Dirichlet allocation (LDA) method is then utilized to further group and discover the features. The text-mining results provide evidence for the development characteristics and trends of industrial product e-commerce in China.

Prevalence of vaginal and cervical HPV infection among 35-year age cohort ever-married women in Kalutara district of Sri Lanka and the validity of vaginal HPV/DNA specimen as a cervical cancer screening tool: a cross-sectional study.

Cervical cancer is the 2nd most common female cancer among Sri Lankan females and is almost associated with sexually transmitted cervicovaginal human papillomavirus (HPV) infection. The study objectives were to determine the prevalence of vaginal and cervical HPV infection among 35year old ever-married women and assess the validity of primary healthcare provider-collected vaginal HPV/DNA specimens as a cervical cancer screening tool to improve the coverage of the programme. A descriptive cross-sectional study was carried out from the 1st of September 2018 to the 31st of January 2019. Ever-married women 35 years of age in Kalutara district were the study population. Two women from each Public Health Midwife area (n = 413) were selected randomly from the relevant area eligible families register/s. HPV/DNA cervical specimen and vaginal specimen collection (n = 621) were carried out. Specimens were screened by the Cobas 4800 HPV/DNA automated Polymerase Chain Reaction (PCR) machine. Participants' profiles were recorded by the research assistants using an interviewer-administered questionnaire. The overall prevalence of vaginal and cervical HPV infection was 7.08% (95% CI; 5.2-9.4%) and 6.12% (95% CI; 4.26-8.3%) respectively. Sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), diagnostic accuracy, and the kappa coefficient of the vaginal HPV/DNA screening method vs. cervical HPV/DNA screening method were 100%, 98.9%, 86.4%, 100%, 99% and 0.92 respectively. Vaginal HPV/DNA specimen screening method can be used as a cervical cancer screening tool due to its high validity. Pilots of the feasibility should be set up before the regional or national rollout of vaginal sampling strategies.