Detection Of Cervical Cancer Research Articles

Determinants of Childbearing Age Couples Perform Early Detection of Cervical Cancer Through IVA Method (Visual Inspection of Acetic Acid) in Sigi Regency

Introduction: Cervical cancer is a malignant disease that is quite often heard among the public. Cervical cancer or commonly referred to as cervical cancer often occurs in women. Cervical cancer can occur due to a poor lifestyle and environment, such as having free sex, changing partners and a lack of personal hygiene. Objective: This study aims to determine the determinants of early detection of cervical cancer in couples of childbearing age (PUS) in Sigi Regency. Method: This study used a cross sectional research design. Result: There was a significant relationship between knowledge, attitude and behavior of early detection of cervical cancer in Sigi Regency. There was no significant relationship between education, employment and support of health workers and early detection behavior of cervical cancer in Sigi Regency. Conclusion: This study concluded that there is a significant relationship between knowledge, attitudes and behaviors for early detection of cervical cancer in Sigi Regency. And there was no significant relationship between education, employment and support of health workers and early detection behavior of cervical cancer in Sigi Regency.

Evaluation of a real-time optoelectronic method for the detection of cervical intraepithelial neoplasia and cervical cancer in patients with different transformation zone types

We aimed to evaluate the diagnostic value of TruScreen, a real-time diagnostic technology, for cervical lesions in patients with different transformation zone (TZ) types. A total of 1908 women aged 34.0 ± 7.3 years who have received cytology, human papillomavirus (HPV) testing, TruScreen, and colposcopy were recruited. The clinical performances of these tests were evaluated for their detection of high-grade squamous intraepithelial lesion (HSIL), adenocarcinoma in situ (AIS), or more severe lesions in patients with different TZ types. For the detection of HSIL, AIS, or more severe lesions, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of TruScreen were 65.08%, 64.76%,11.55%, and 96.33%, respectively, which were similar to cytology (all P values > 0.05). For the detection of HSIL + in patients with type 3 TZ, the sensitivity, specificity, PPV, and NPV of TruScreen were 72.29%, 67.59%, 13.86%, and 97.13%, respectively, which were significantly higher than the sensitivity (51.16%, P = 0.029), specificity (59.59%, P = 0.001), PPV (7.94%, P = 0.016), and NPV (94.71%, P = 0.049) in type 1 and type 2 TZs. TruScreen has detection accuracy comparable to cytology and performs even better in patients with type 3 TZ.

The Distribution of HR-HPV E6/E7 DNA and mRNA by Histological Grade and the Clinical Performance for Detection of Cervical Cancer and Precancer.

High-risk human papillomavirus (HR-HPV) testing, utilizing both DNA and RNA methods, offers enhanced sensitivity compared to cytology for detecting high-grade cervical intraepithelial neoplasia (CIN2+). Meanwhile, HR-HPV E6 and E7 mRNAs are more likely to differentiate the transient infection from the persistent than DNA. Aptima HPV can not only detect HPV mRNA but also HPV DNA though it is much more efficient at detecting HPV RNA than DNA. Currently, there are few studies on the distribution of HPV E6 and E7 mRNA and DNA in the same individual. It is interesting to compare the clinical performance of the Onclarity and Aptima HPV assays and to assess variations in viral load across different histological grades at both DNA and mRNA levels. The analysis included 1607 women (902 from a cervical cancer screening population and 705 inpatients and outpatients), with cervical cytological samples tested using the Aptima and Onclarity HPV assays. Both assays demonstrated high agreement for HPV types 18/45 and 16. Signal-to-cutoff (S/CO) values and Ct values for various HR-HPV types increased with histological severity from normal tissue to cancer. Notably, HPV18 Ct values exceeded those for HPV16 and 45 in women with ≥ CIN1 lesions but decreased sharply in cancer cases. Across the screening population, both assays showed similar sensitivity and predictive values for detecting CIN2+ lesions. The area under the curve (AUC) for CIN2+ and CIN3+ detection in the study population was robust (CIN2+: 0.880, 0.863; CIN3+: 0.881, 0.863). The DNA level for various HR-HPV types increased with histological severity from normal tissue to cancer, which might impact the performance of Aptima HPV assay. Both assays showed similar sensitivity and predictive values for detecting CIN2+ lesions.

Optimizing cervical cancer classification using transfer learning with deep gaussian processes and support vector machines

BackgroundCervical cancer is the fourth most frequent cancer in women worldwide. Even though cervical cancer deaths have decreased significantly in Western countries, low and middle-income countries account for nearly 90% of cervical cancer deaths. While Western countries are leveraging the powers of artificial intelligence (AI) in the health sector, most countries in sub-Saharan Africa are still lagging. In Uganda, cytologists manually analyze Pap smear images for the detection of cervical cancer, a process that is highly subjective, slow, and tedious. Machine learning (ML) algorithms have been used in the automated classification of cervical cancer. However, most of the MLs have overfitting limitations which limits their deployment, especially in the health sector where accurate predictions are needed.MethodsIn this study, we propose two kernel-based algorithms for automated detection of cervical cancer. These algorithms are (1) an optimized support vector machine (SVM), and (2) a deep Gaussian Process (DGP) model. The SVM model proposed uses an optimized radial basis kernel while the DGP model uses a hybrid kernel of periodic and local periodic kernel.ResultsExperimental results revealed accuracy of 100% and 99.48% for an optimized SVM model and DGP model respectively. Results on precision, recall, and F1 score were also reported.ConclusionsThe proposed models performed well on cervical cancer detection and classification, and therefore suitable for deployment. We plan to deploy our proposed models in a mobile application-based tool. The limitation of the study was the lack of access to high-performance computational resources.

Vaginal self-sampling for HPV in the context of cervical cancer screening

Abstract Background Effective cervical cancer screening programme has the potential to improve disease outcomes, yet women’s participation rates in Latvia remain suboptimal. Utilizing vaginal self-sampling for HPV, a convenient method, has demonstrated efficacy in boosting participation in under-screened populations. We analysed sociodemographic factors, as well as health behaviours with the preference for vaginal self-sampling procedures for early detection of cervical cancer. Methods Cross-sectional survey (2021-2022) included 1313 women in Latvia. Sampling was done in the colposcopy clinic and among GP practices. In the univariate analysis cervical cancer examination preference (self-test or by a physician) was analysed in association sociodemographic factors, participation in the screening, HPV status, study group, and health-related behaviour. Financed by “Internal consolidation of RSU and external consolidation of RSU with LSPA” (No. 5.2.1.1.i.0/2/24/I/CFLA/005), The EU Recovery and Resilience plan and the state budget, Grant Nr. RSU-PAG-2024/1-0016. Results 48.6 % (n = 538) of the women would prefer to use a vaginal self-test. Higher odds of the vaginal self-test preference were observed among Latvian (OR = 1.4 (1.1-1.8) vs other nationality women, but no other sociodemographic factors showed statistically significant associations. Women in the colposcopy study group (vs GP practices) were more likely to utilize self-sampling (OR = 1.8 (1.4-2.5). Non-participation in cervical cancer screening was related to 2.4 (1.6-3.6) higher odds of self-test preference, but knowledge about screening was related to 1.5 (1.1-2.0) times higher odds. Women who were HPV-negative were more likely to prefer vaginal self-test for HPV (OR = 1.4 (1.1-1.8) in comparison to HPV-positive women. Health-related behaviour did not show any associations. Conclusions Vaginal self-test for HPV can be effectively used to reach under-screened populations and enhance cervical cancer screening coverage. Key messages • The implementation of vaginal self-sampling for HPV testing has the potential to improve participation rates in cervical cancer screening programs among under-screened populations. • Outreach and education activities tailored to specific target groups in population could enhance level of the cervical cancer screening uptake.

Metasurface Based Surface Plasmon Resonance (SPR) Biosensor for Cervical Cancer Detection with Behaviour Prediction using Machine Learning Optimization Based on Support Vector Regression

Metasurface Based Surface Plasmon Resonance (SPR) Biosensor for Cervical Cancer Detection with Behaviour Prediction using Machine Learning Optimization Based on Support Vector Regression

Facile Electrical DNA Genosensor for Human Papillomavirus (HPV 58) for Early Detection of Cervical Cancer

For decades, a Pap smear test has been applied as a conventional method in detecting Human Papillomavirus caused cervical cancer. False-positive results were also recorded while using it as conventional method. Current biosensor such as Hybrid (II) Capture resulted in higher time consumption and cost. s Meanwhile, in this study we provided facile, mini, rapid, highly sensitive, eco-friendly, and cost-effective sensing system focusing on HPV strain 58 (HPV58) in a nano-size lab-on-chip technology genosensor. 30-mer of virus ssDNA designed and analyzed as a probe via bioinformatics tools such as GenBank, Basic Local Alignment Searching Tools (BLAST) and ClustalW. Nanotechnology-developed colloidal Gold-nanoparticles (AuNPs) are used in the biosensor fabrication to produce high stability and electron efficient transmission during electrical measurement. AuNPs-APTES modified on active sites of IDEs, followed by immobilization of specific probe ssDNA for HPV 58. Hydrogen binding during hybridization with its target produce electrical signals measured by KEITHLEY 2450 (Source Meter). The genosensor validated with different types of targets such as complimentary, non-complementary and single mismatch oligonucleotides. The serial dilution of target concentration has been experimented triplicate (n=3) range from 1fM to 10μM. The slope of calibration curve resulted 2.389E-0 AM-1 with regression coefficient (R2) = 0.97535.

Differential evolution optimization based ensemble framework for accurate cervical cancer diagnosis

Cervical cancer remains a significant global health concern, demanding accurate and efficient diagnostic approaches for early detection and treatment. However, there are situations where a single deep learning model might not be sufficient to adequately capture the pertinent information required for precise disease prediction from intricate datasets. In this paper, we introduce an innovative ensemble learning framework that leverages the Differential Evolution (DE) algorithm to enhance the detection of cervical cancer. Our innovative approach combines the collective strength of a diverse set of base models using feature fusion techniques to achieve precise and robust classification. We have developed three base models, denoted as Fusion 1, Fusion 2, and Fusion 3, where each fusion model incorporates two pre-trained models using a feature fusion technique. To capture sequential dependencies and improve feature attention, we have integrated ConvLSTM layers and Squeeze-and-Excitation (SE) blocks into these base models. Subsequently, we've amalgamated the predictions of each base model using a weighted aggregation scheme, with the weights optimized using the DE algorithm. Our ensemble framework introduces a novel method for dynamic weight adjustment, utilizing advanced fusion techniques to improve cervical cancer detection accuracy. This approach ensures robust diagnostic performance across cancer cells datasets, enhancing patient outcomes and community health. Our evaluation covers two datasets, SIPaKMeD and Mendeley LBC, demonstrating the remarkable performance and robustness of our ensemble model. It consistently outperforms individual base models and even surpasses state-of-the-art methods, achieving an impressive accuracy rate of 98.96 % on the Mendeley LBC dataset and 95.68 % on the SIPaKMeD dataset. The incorporation of ConvLSTM layers, SE blocks, and DE optimization significantly contributes to the model's exceptional accuracy, its ability to generalize effectively, and its adaptability to diverse scenarios. Additionally, we employ Grad-CAM to visualize how the base models focus on crucial regions for accurate predictions, providing insights into the model's decision-making process. Our ensemble model exhibits outstanding Area under the Curve (AUC) values in Receiver Operating Characteristic (ROC) analysis, further confirming its effectiveness. This research represents a significant advancement in cervical cancer detection, underscoring the potential of ensemble learning techniques optimized through DE for enhancing diagnostic accuracy and advancing patient care.

Mathematical Evaluation of Deep Learning Architecture with Feature Fusion for Cervical Cancer Detection Classification

Cervical cancer is still one of the main reasons women die around the world, which shows how important it is to have accurate and quick ways to diagnose the disease. This study looks into how to improve the accuracy of finding cervical cancer using a deep learning-based classification system that combines features. In this mixed classic feature extraction methods, like Histogram of Oriented Gradients (HOG) and Scale-Invariant Feature Transform (SIFT), with deep learning architectures, like Graph Convolutional Networks (GCNs) and Capsule Networks. Each of these added its own benefits to the fusion model. Both HOG and SIFT are good at capturing important texture and structure features, even when the image conditions change. GCNs are used to learn relationship data between picture areas. This helps get a better sense of how things fit together in space, which is very important for medical imaging. Capsule Networks, on the other hand, let you understand the subtleties of hierarchical patterns in pictures of cervical cells. They do this by looking at spatial hierarchies and rotational changes that are very important for finding cancer. Our suggested fusion model combines these multi-level features, taking advantage of how the best features of deep learning and standard learning methods work together. Validation on standard cervical cancer image datasets showed that this fusion approach was much more accurate and precise at classifying than individual methods. Quantitative testing showed that the fusion model had higher sensitivity and specificity, which shows that it can reduce the number of fake negatives and positives, which is very important in clinical diagnosis. Our results show that the feature fusion model not only gives us a strong and accurate way to classify cervical cancer, but it also lays the groundwork for more uses in other complicated areas of medical imaging.

Development of a Terahertz Metamaterial Micro-Biosensor for Ultrasensitive Multispectral Detection of Early Stage Cervical Cancer

Development of a Terahertz Metamaterial Micro-Biosensor for Ultrasensitive Multispectral Detection of Early Stage Cervical Cancer

Early Cervical Cancer Diagnosis with SWIN-Transformer and Convolutional Neural Networks.

Introduction: Early diagnosis of cervical cancer at the precancerous stage is critical for effective treatment and improved patient outcomes. Objective: This study aims to explore the use of SWIN Transformer and Convolutional Neural Network (CNN) hybrid models combined with transfer learning to classify precancerous colposcopy images. Methods: Out of 913 images from 200 cases obtained from the Colposcopy Image Bank of the International Agency for Research on Cancer, 898 met quality standards and were classified as normal, precancerous, or cancerous based on colposcopy and histopathological findings. The cases corresponding to the 360 precancerous images, along with an equal number of normal cases, were divided into a 70/30 train-test split. The SWIN Transformer and CNN hybrid model combines the advantages of local feature extraction by CNNs with the global context modeling by SWIN Transformers, resulting in superior classification performance and a more automated process. The hybrid model approach involves enhancing image quality through preprocessing, extracting local features with CNNs, capturing the global context with the SWIN Transformer, integrating these features for classification, and refining the training process by tuning hyperparameters. Results: The trained model achieved the following classification performances on fivefold cross-validation data: a 94% Area Under the Curve (AUC), an 88% F1 score, and 87% accuracy. On two completely independent test sets, which were never seen by the model during training, the model achieved an 80% AUC, a 75% F1 score, and 75% accuracy on the first test set (precancerous vs. normal) and an 82% AUC, a 78% F1 score, and 75% accuracy on the second test set (cancer vs. normal). Conclusions: These high-performance metrics demonstrate the models' effectiveness in distinguishing precancerous from normal colposcopy images, even with modest datasets, limited data augmentation, and the smaller effect size of precancerous images compared to malignant lesions. The findings suggest that these techniques can significantly aid in the early detection of cervical cancer at the precancerous stage.

ATTITUDE OF FEMALE STUDENTS IN PUBLIC TERTIARY INSTITUTION IN IMO ABOUT CERVICAL CANCER SCREENING

Cervical cancer is a significant health concern and one of the leading causes of death among women globally. This study aimed to examine the attitudes related to cervical cancer screening among female students in public tertiary institutions in Imo State, Nigeria. The study, guided by three research questions and two null hypotheses tested at the 0.05 significance level used a descriptive survey design. A sample of 900 students was selected from a population of 11,825 female undergraduates. The research instrument, “Attitude towards Cervical Cancer Screening Questionnaire (ACCSQ)” was validated and found reliable with coefficient alphas of 0.89. Data were collected through direct delivery and analysed using SPSS, employing descriptive statistics of mean and standard deviation and inferential statistics of ANOVA. The findings revealed that most students had a positive attitude toward screening, with a mean attitude score of 53.35. Attitudes of the female students of this study towards cervical cancer screening did not significantly differ based on their ages or their level of education. The study recommended that given the generally positive attitude towards cervical cancer screening, awareness campaigns should be strengthened to further encourage screening participation. These campaigns should target all age groups, emphasizing the importance of early detection and regular screening for cervical cancer. KEYWORDS: Cervical cancer, screening, female students, attitude, public, tertiary institutions

Characterizing the Patterns of Cervical Cancer Symptom Recognition, Symptom Response, and Associated Factors Among Patients Treated in a Teaching Hospital in Ghana.

Cervical cancer is a major global health issue and ranks as the second leading cause of cancer-related deaths among women in Ghana. This study aimed to explore and characterize the patterns of symptom recognition associated with cervical cancer and the symptom responses among women in Ghana. A descriptive qualitative design utilizing 20 individual semistructured interview sessions was used. The study was conducted in one of Ghana's major cancer treatment centers. Data were collected using face-to-face interviews. The data were analyzed using NVivo 12 and presented as themes and subthemes. Data analysis revealed 2 main themes: barriers to symptom recognition and response and facilitators of early symptom recognition and symptom response. Barriers included deficient knowledge about cervical symptoms, spiritual attributions of symptoms, preference for herbal remedies for symptoms, misdiagnosis, and seeking help through multiple facility visits. Facilitating factors of symptom response include perceived severity/identification of additional symptoms, quick referrals with some navigation within the healthcare system, and advice from women's microcommunity. The study emphasizes the need for continuous educational efforts on cervical cancer and its symptoms. Healthcare providers, patients, and the public have a part to play in the awareness and early detection of cervical cancer. Initiatives that educate women about the early symptoms of cervical cancer and the importance of screening can help with early recognition. Educating communities about cervical cancer empowers individuals to take charge of their health and encourages supportive environments for women to seek care.

Diagnostic potential of miRNA-135A1 in human papillomavirus associated cervical lesions

Introduction. Human papillomavirus (HPV) infection with high-risk HPVs is an etiological factor in the development of cervical cancer, with HPV type 16 (HPV16) being the most common. The mechanisms leading to disruption of viral oncogene expression and initiation of epithelial cell transformation are poorly understood. Epigenetic regulatory factors, including cellular miRNAs, may play an important role in HPV-induced carcinogenesis, and aberrantly expressed miRNAs may be promising markers for the diagnosis of HPV-associated lesions.Aim. To search for miRNAs involved in the pathogenesis of HPV16-associated cervical cancer and to evaluate their diagnostic potential for the detection of cervical cancer and precancerous lesions.Materials and methods. MiRNA expression in clinical samples was assessed by both next generation sequencing and quantitative stem-loop polymerase chain reaction (sl-qPCR). Plasma miRNAs from patients with precancerous and cancerous lesions and healthy donors were analyzed using sl-qPCR. Loss of heterozygosity in cervical cancer samples was assessed by copy number ratio of MIR135A1 and ACTB genes. A total of 67 patients with cervical cancer, 21 with precancerous cervical lesions and 24 healthy donors were included in the study. The effect of DNA methylation on miRNA-135A1 expression was evaluated after treatment with a demethylating agent of the cervical HPV16-positive SiHa cell line. Changes in the expression of the HPV16 E6 oncogene were analyzed after transfection with synthetic analogues of the mature forms of miRNA-135А1 (miRNA-135a-3p and miRNA-135a-5p).Results. A significant decrease in the expression of miRNA-135A1 and miRNA-135A2 was detected in tumor tissue samples from HPV16-positive cervical cancer, which was confirmed by sl-qPCR in an independent panel of tumor samples. A decrease in miRNA-135A1 expression was shown to result from both loss of heterozygosity of the gene and aberrant DNA methylation. Transfection of mature forms of miRNA-135A1 into SiHa cells resulted in decreased expression of the E6 oncogene of HPV16. Blood plasma samples from patients with cervical cancer and precancerous lesions showed lower levels of miRNA-135a-3p than healthy donors, and ROC analysis indicated its high diagnostic potential.Conclusion. Levels of miRNA-135A1 are significantly reduced in cervical lesions, both in tumor tissue and plasma, and the ability of this miRNA to suppress the expression of the HPV16 E6 oncogene suggests its oncosuppressive properties. Thus, miRNA-135A1 can be used as a promising new marker for the diagnosis of HPV-associated lesions.

Enhancing awareness of breast self-examination and pap smears for early detection of breast and cervical cancer

Reproductive health problems, especially breast cancer and cervical cancer are the most common cancers diagnosed in women in Indonesia. Currently, several testing methods to detect breast and cervical cancer early, such as breast self-examination (BSE) and pap smears, have been used to reduce cancer risk factors. However, these two methods are still not widely used. Outreach activities have been proven to increase knowledge about the importance of BSE and pap smears in women. This community service program aims to increase knowledge about the causes and symptoms of breast and cervical cancer, as well as early detection using BSE and pap smears. This service activity plan consisted of preparation, implementation, and evaluation stages. The method used consists of delivering interactive material, discussion, and practice. This activity was attended by 38 participants, consisting of women from PKK cadres in the Andir area, Ciroyom District, the majority of whom were over 35 years old. Based on the results of the post-test, this community service activity was successful in increasing participants' knowledge, attitudes, and behavior towards breast and cervical cancer as well as the early detection methods of BSE and pap smears.

Spatially Resolved Fibre-Optic Probe for Cervical Precancer Detection Using Fluorescence Spectroscopy and PCA-ANN-Based Classification Algorithm: An In Vitro Study.

Cervical cancer can be detected at an early stage through the changes occurring in biochemical and morphological properties of epithelium layer. Fluorescence spectroscopy has the ability to identify these subtle changes non-invasively and in real time with good accuracy in comparison with conventional techniques. In this paper, we report the usage of a custom designed spatially resolved fibre-optic probe (SRFOP), which consists of 77 fibres in two concentric rings, for the detection of cervical cancer using fluorescence spectroscopy technique. The aim of this study is to classify different grades of cervical precancer on the basis of their fluorescence spectra followed by a robust classification algorithm. Fluorescence spectra of 28 cervical tissue samples of different categories have been recorded using six detector fibres of FOP at different spatial locations with the source fibre (SF). A 405 nm laser diode source has been utilised to excite the samples and a USB 4000 Ocean Optics spectrometer to collect the output spectra in the wavelength range 400-700 nm. Principal component analysis (PCA) was applied to the collected spectra to reduce the dimensionality of the data while preserving the most significant features for classification. The first 10 principal components, which captured the majority of the variance in the spectra, were selected as input features for the classification model. Classification was then performed using an artificial neural network (ANN) with a specific architecture, including an input layer, hidden layers, and a softmax activation function in the output layer. Experimental and classification results both demonstrate that proximal fibres (PFs) perform better than distal fibres (DFs) in capturing the discriminatory features present in the epithelium layer of cervical tissue samples as PF collect most of the signal from the epithelium layer. The combined approach of spatially resolved fluorescence spectroscopy and PCA-ANN classification techniques is able to discriminate different grades of cervical precancer and normal with an average sensitivity, specificity and accuracy of 93.33%, 96.67% and 95.57%, respectively.

Comprehensive Details on Human Papillomavirus (HPV) Infections and Associated Malignancies: Awareness about Prophylaxis & Treatment Options Available for HPV Infections

Human Papilloma virus (HPV) role has now been widely accepted as a causative agent for cervical as well as head and neck squamous cell carcinomas. Screening and early detection of cervical cancer remains the key element to eradicate this deadly disease. Since it has a long natural history and disease progression, this gave an opportunity for early detection through screening of precancerous lesions which was adopted in high income countries (HIC) like UK which has led to the significant reduction of the cases. Unfortunately, Low- and middle-income countries are facing huge burden because of the lack of effective screening program. FDA approved Cervarix, Gardasil and Gardasil 9 are used as prophylaxis for cervical cancer & genital warts but screening is still essential after vaccination because these vaccines are not effective against all types of HPV types. HPV 16 & HPV 18 are highly oncogenic types and accounts for 70% of cervical cancers. The use of vaccine reduces the risk of getting HPV infection and decrease the rate of morbidity and mortality due to the cervical cancer. In addition to vaccines, many peptides or protein-based & cell or DNA-based vaccines are still in clinical trials; these prevention and management available in vaccines are likely to come up with significant benefits of health in future. Although it’s usually cured by immune system but presence of certain cofactors such as smoking, HIV etc. reduces the probability of an individual to eradicate the infection effectively. The aim of this study is to review literature regarding HPV related infections and malignancies. Moreover, it will make individuals aware about prophylaxis & treatment options available for HPV infection. This review article evaluates the HPV related diseases, there screening, evaluation and management currently available. Bangladesh Journal of Medical Science Vol. 23 No. 04 October’24 Page : 967-983

Review to Elucidate the Correlation between Cuproptosis-Related Genes and Immune Infiltration for Enhancing the Detection and Treatment of Cervical Cancer.

Copper is a vital trace element in oxidized and reduced forms. It plays crucial roles in numerous biological events such as redox chemistry, enzymatic reactions, mitochondrial respiration, iron metabolism, autophagy, and immune modulation. Maintaining the balance of copper in the body is essential because its deficiency and excess can be harmful. Abnormal copper metabolism has a two-fold impact on the development of tumors and cancer treatment. Cuproptosis is a form of cell death that occurs when there is excessive copper in the body, leading to proteotoxic stress and the activation of a specific pathway in the mitochondria. Research has been conducted on the advantageous role of copper ionophores and chelators in cancer management. This review presents recent progress in understanding copper metabolism, cuproptosis, and the molecular mechanisms involved in using copper for targeted therapy in cervical cancer. Integrating trace metals and minerals into nanoparticulate systems is a promising approach for controlling invasive tumors. Therefore, we have also included a concise overview of copper nanoformulations targeting cervical cancer cells. This review offers comprehensive insights into the correlation between cuproptosis-related genes and immune infiltration, as well as the prognosis of cervical cancer. These findings can be valuable for developing advanced clinical tools to enhance the detection and treatment of cervical cancer.

The Future of Cervical Cancer Screening.

Cervical cancer remains a significant health concern, particularly in developing countries, where it is a leading cause of cancer-related deaths among women. Innovative technologies have emerged to improve the efficiency, cost-effectiveness, and sensitivity of cervical cancer screening and treatment methods. This study aims to explore the various approaches for the detection and treatment of human papillomavirus (HPV), cervical dysplasia (CD), and cervical cancer, highlighting new technologies and updated screening strategies in developing areas. A comprehensive literature search was conducted using PubMed to identify relevant publications on the subject of cervical cancer screening and HPV detection. HPV infection and cervical cancer continue to pose significant global health challenges. Emerging technologies such as rapid, low-cost HPV testing combined with high-resolution digital colposcopy and artificial intelligence interpretation hold promise for efficient and sensitive screening. Advancements in HPV vaccine distribution, high-risk HPV screening, DNA methylation assays, dual-stain cytology, lab-on-chip assays, and deep learning technologies offer new avenues for improved detection and risk stratification.Research and innovations in detection and treatment methods are crucial for reducing the burden of these diseases worldwide. Screening for HPV and CD plays a pivotal role in reducing the risk of cervical cancer-related mortality. The development of novel technologies, along with efforts to enhance global health equity and integrate cervical cancer prevention with HIV screening and treatment programs, represent critical steps toward achieving comprehensive cervical cancer screening on a global scale.

Cost-effectiveness analysis of alternative screening strategies for the detection of cervical cancer among women in rural areas of Western Kenya.

While the incidence of cervical cancer has dropped in high-income countries due to organized cytology-based screening programs, it remains the leading cause of cancer death among women in Eastern Africa. Therefore, the World Health Organization (WHO) now urges providers to transition from widely prevalent but low-performance visual inspection with acetic acid (VIA) screening to primary human papillomavirus (HPV) DNA testing. Due to high HPV prevalence, effective triage tests are needed to identify those lesions likely to progress and so avoid over-treatment. To identify the optimal cost-effective strategy, we compared the VIA screen-and-treat approach to primary HPV DNA testing with p16/Ki67 dual-stain cytology or VIA as triage. We used a Markov model to calculate the budget impact of each strategy with incremental quality-adjusted life years and incremental cost-effectiveness ratios (ICER) as the main outcome. Deterministic cost-effectiveness analyses show that the screen-and-treat approach is highly cost-effective (ICER 2469 Int$), while screen, triage, and treat with dual staining is the most effective with favorable ICER than triage with VIA (ICER 9943 Int$ compared with 13,177 Int$). One-way sensitivity analyses show that the results are most sensitive to discounting, VIA performance, and test prices. In the probabilistic sensitivity analyses, the triage option using dual stain is the optimal choice above a willingness to pay threshold of 7115 Int$ being cost-effective as per WHO standards. The result of our analysis favors the use of dual staining over VIA as triage in HPV-positive women and portends future opportunities and necessary research to improve the coverage and acceptability of cervical cancer screening programs.