Treatment Of Early Cancer Research Articles

Long Non-coding RNAs Regulating Macrophage Polarization in Liver Cancer.

Primary liver cancer is the second leading cause of cancer-related death worldwide. At present, liver cancer is often in an advanced stage once diagnosed, and treatment effects are generally poor. Therefore, there is an urgent need for other powerful treatments. Macrophages are an important component of the tumor microenvironment, and macrophage polarization is crucial to tumor proliferation and differentiation. Regulatory interactions between macrophage subtypes, such as M1 and M2, lead to a number of clinical outcomes, including tumor progression and metastasis. So, it is important to study the drivers of this process. Long non-coding RNA has been widely proven to be of great value in the early diagnosis and treatment of tumors. Many studies have shown that long non-coding RNA participates in macrophage polarization through its ability to drive M1 or M2 polarization, thereby participating in the occurrence and development of liver cancer. In this article, we systematically elaborated on the long non-coding RNAs involved in the polarization of liver cancer macrophages, hoping to provide a new idea for the early diagnosis and treatment of liver cancer. Liver cancer- related studies were retrieved from PubMed. Based on our identification of lncRNA and macrophage polarization as powerful therapies for liver cancer, we analyzed research articles in the PubMed system in the last ten years on the crosstalk between lncRNA and macrophage polarization. By targeting M1/M2 macrophage polarization, lncRNA may promote or suppress liver cancer, and the references are determined primarily by the article's impact factor. Consequently, the specific mechanism of action between lncRNA and M1/M2 macrophage polarization was explored, along with the role of their crosstalk in the occurrence, proliferation, and metastasis of liver cancer. LncRNA is bidirectionally expressed in liver cancer and can target macrophage polarization to regulate tumor behavior. LncRNA mainly functions as ceRNA and can participate in the crosstalk between liver cancer cells and macrophages through extracellular vesicles. LncRNA can potentially participate in the immunotherapy of liver cancer by targeting macrophages and becoming a new biomolecular marker of liver cancer.

Skin cancer management: Making the most of your pathologist.

Australia has the highest incidence of skincancer globally. Early detection and treatment of skin cancer is critical for positive patient outcomes. General practitioners (GPs) play a central role in skin cancer management in Australia. Collaboration between GPs and pathologists can improve the accuracy ofskin cancer diagnosis. However, for improvement to occur, clear communication and high-quality specimens are essential. Inadequate clinical information and suboptimal biopsy specimens can hinder diagnosis. Improved communication, targeted training and selecting appropriate biopsy techniques are essential. A collaborative approach, guided by recommended techniques and clear guidelines, can minimise errors and improve patient outcomes in Australia's GP-led skin cancer management system.

Application of acid-activated near-infrared viscosity fluorescent probe targeting lysosomes in cancer visualization

The higher viscosity and lower pH in lysosomes of cancer cells highlight their potential as biomarkers for cancer. Therefore, the development of acid-activated viscosity fluorescent probes is significant for the early diagnosis and treatment of cancer. Based on this, we have designed and synthesized a near-infrared fluorescent probe based on the 2-(2-hydroxyphenyl)benzothiazole (HBT) group, namely HBTH, to monitor the viscosity changes within lysosomes. It has been demonstrated that HBTH was extremely sensitive to viscosity, with a strong linear relationship between fluorescence intensity and log(viscosity) within the range of (logη) = 0–3.06 (a correlation coefficient of 0.98), proving its capability for quantitative viscosity measurement. In particular, the most obvious fluorescence enhancement of HBTH was only efficiently triggered by the combined effect of low pH and high viscosity. Furthermore, HBTH can rapidly localize to lysosomes by wash-free procedure at a low concentration (100 nM) and achieve high-fidelity imaging within 20 s. It can also monitor the dynamic processes of lysosomes in cells, viscosity changes under drug stimuli, and lysosomal behavior during mitophagy. Importantly, HBTH is capable of identifying tumors in tumor-bearing nude mice through in vivo imaging. These features make HBTH a powerful tool for the early diagnosis and treatment of cancer.

Impact of primary endoscopic resection on oncological outcomes after esophagectomy for cancer: a retrospective propensity score-based cohort study.

Esophageal cancer posed significant global health challenges, particularly due to poor survival rates, especially in advanced stages. Primary endoscopic resection had emerged as an alternative treatment for early esophageal cancer, aiming to preserve organ function and reduce surgical morbidity. This retrospective multicenter cohort study included 334 patients with early esophageal cancer (T1a-b, N0) from 30 French-speaking European centers between 2000 and 2010. Patients underwent either primary endoscopic resection followed by esophagectomy (E group, n = 36) or esophagectomy alone (S group, n = 298). Cox proportional hazards models adjusted for TNM stage and propensity score weighting were used to assess the impact of primary endoscopic resection on recurrence-free survival (RFS), overall survival (OS), and postoperative complications. Primary endoscopic resection did not significantly influence RFS (adjusted HR 0.92, 95% CI 0.31 to 2.68, p = 0.88) or OS (adjusted HR 1.06, 95% CI 0.35 to 3.13, p = 0.92) compared to esophagectomy alone. Initial higher thromboembolic complications in the endoscopic resection group were not significant after adjustment (adjusted OR 4.73, 95% CI 0.34 to 64.27, p = 0.24). Primary endoscopic resection followed by esophagectomy for early esophageal cancer did not alter oncological outcomes or overall survival in this retrospective cohort. These findings supported the role of primary endoscopic resection as a safe initial treatment strategy, warranting validation in larger prospective studies. Our study was registered retrospectively on the Clinicaltrials.com website under the identifier NCT01927016. We acknowledge the importance of prospective registration and regret that this was not done before the commencement of the study.

Latest Developments in Early Detection and Effective Treatment of Cancer: A Meeting Report.

Despite a lower estimated rate of cancer incidence in Iran compared to the global average, the trend is unfortunately increasing. This necessitates the implementation of early detection of cancer and targeted therapies to effectively treat various types of cancer. Therefore, the 5th "International Royan Cancer Conference: From Bench to Bedside" was held to focus on critical cancer-related aspects such as gene- and cell therapy, immunotherapy, oligonucleotides in cancer treatment, biosensors for detection, and drug delivery. The 2-day conference took place in February 2024 at the Royan Institute, Tehran. This collaborative effort brought together experts from both basic and clinical research fields. The primary objective of the conference was to address clinical challenges and harness the potential of basic sciences for early cancer diagnosis and treatment, with a robust emphasis on ethical considerations. The conference aimed to ensure optimal patient care while advancing scientific understanding in the field and facilitating effective research collaborations among researchers and enthusiasts dedicated to combating cancer.

Deep learning in pulmonary nodule detection and segmentation: a systematic review.

The accurate detection and precise segmentation of lung nodules on computed tomography are key prerequisites for early diagnosis and appropriate treatment of lung cancer. This study was designed to compare detection and segmentation methods for pulmonary nodules using deep-learning techniques to fill methodological gaps and biases in the existing literature. This study utilized a systematic review with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, searching PubMed, Embase, Web of Science Core Collection, and the Cochrane Library databases up to May 10, 2023. The Quality Assessment of Diagnostic Accuracy Studies 2 criteria was used to assess the risk of bias and was adjusted with the Checklist for Artificial Intelligence in Medical Imaging. The study analyzed and extracted model performance, data sources, and task-focus information. After screening, we included nine studies meeting our inclusion criteria. These studies were published between 2019 and 2023 and predominantly used public datasets, with the Lung Image Database Consortium Image Collection and Image Database Resource Initiative and Lung Nodule Analysis 2016 being the most common. The studies focused on detection, segmentation, and other tasks, primarily utilizing Convolutional Neural Networks for model development. Performance evaluation covered multiple metrics, including sensitivity and the Dice coefficient. This study highlights the potential power of deep learning in lung nodule detection and segmentation. It underscores the importance of standardized data processing, code and data sharing, the value of external test datasets, and the need to balance model complexity and efficiency in future research. Deep learning demonstrates significant promise in autonomously detecting and segmenting pulmonary nodules. Future research should address methodological shortcomings and variability to enhance its clinical utility. Deep learning shows potential in the detection and segmentation of pulmonary nodules. There are methodological gaps and biases present in the existing literature. Factors such as external validation and transparency affect the clinical application.

Prediction Model and Nomogram of Early Recurrence of Hepatocellular Carcinoma after Ultrasound-guided Microwave Ablation

Ultrasound-guided microwave ablation (MWA) is recommended as a first-line treatment for early liver cancer due to its minimally invasive, efficient, and cost-effective nature. It utilizes microwave radiation to heat and destroy tumor cells as a local thermal therapy and offers the benefits of being minimally invasive, repeatable, and applicable to tumors of various sizes and locations. However, despite the efficacy of MWA, early recurrence after treatment remains a challenge, particularly when it occurs within a year and has a significant impact on the prognosis of the patient. This study aimed to identify the risk factors for early recurrence after MWA in patients with hepatocellular carcinoma (HCC) and establish a predictive model. A total of 119 patients with hepatocellular carcinoma (HCC) treated in the Department of Ultrasound at the First Affiliated Hospital of the Air Force Medical University from January, 2020 to April, 2022 were included in this study. Patients were categorized into the early recurrence group and the non-early recurrence group based on whether recurrence occurred within 1 year. We conducted univariate analysis on 29 variables. A predictive model was developed using multiple-factor logistic regression analysis, and a risk column graph was created. A total of 28 patients were included in the early recurrence group, with an early recurrence rate of 23%. Tumor size ≥ 3cm, multiple tumors, AST > 35 U/L, low pathological differentiation, CD34 positive, Ki67 level, quantitative parameters mean transit time (mTT), and rise time (RT) were confirmed as risk factors affecting early recurrence after ablation (P < 0.05). Furthermore, the model constructed based on these 5 predictive factors, including tumor size, tumor number, pathological differentiation, CD34, and quantitative analysis parameter mTT, demonstrated good predictive ability, with an AUC of 0.93 in the training set and 0.86 in the validation set. Our research indicates that the risk column graph can be utilized to predict the risk of early postoperative recurrence in patients after MWA. This contributes to guiding personalized clinical treatment decisions and provides important references for improving the prognosis of patients.

Endoscopic Resections for Barrett's Neoplasia: A Long-Term, Single-Center Follow-Up Study.

Background and Objectives: Endoscopic mucosal resection (EMR) and endoscopic submucosal dissection (ESD) are both well-established and effective treatments for dysplasia and early cancer in Barrett's esophagus (BE). This study aims to compare the short- and long-term outcomes associated with these procedures in treating Barrett's neoplasia. Materials and Methods: This single-center retrospective cohort study included 95 patients, either EMR (n = 67) or ESD (n = 28), treated for Barrett's neoplasia at Sahlgrenska University Hospital between 2004 and 2019. The primary outcome was the complete (en-bloc) R0 resection rate. Secondary outcomes included the curative resection rate, additional endoscopic resections, adverse events, and overall survival. Results: The complete R0 resection rate was 62.5% for ESD compared to 16% for EMR (p < 0.001). The curative resection rate for ESD was 54% versus 16% for EMR (p < 0.001). During the follow-up, 22 out of 50 patients in the EMR group required additional endoscopic resections (AERs) compared to 3 out of 21 patients in the ESD group (p = 0.028). There were few adverse events associated with both EMR and ESD. In both the stratified Kaplan-Meier survival analysis (Log-rank test, Chi-square = 2.190, df = 1, p = 0.139) and the multivariate Cox proportional hazards model (hazard ratio of 0.988; 95% CI: 0.459 to 2.127; p = 0.975), the treatment group (EMR vs. ESD) did not significantly impact the survival outcomes. Conclusions: Both EMR and ESD are effective and safe treatments for BE neoplasia with few adverse events. ESD resulted in higher curative resection rates with fewer AERs, indicating its potential as a primary treatment modality. However, the survival analysis showed no difference between the methods, highlighting their comparable long-term outcomes.

A Linear Relationship between the Number of Cancers among First-Degree Relatives and the Risk of Multiple Primary Cancers.

With advances in the early detection and treatment of cancer, the incidence of multiple primary cancers (MPC) or second primary cancers has increased over time. Characterization of etiologic risk factors, including family history of cancer, within the general population is critical for assessing MPC risk in patients. We examined the association between family history of cancer among first-degree relatives and MPC risk in a prospective study of 139,958 participants from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Cox proportional hazard models were used to calculate HRs and 95% confidence intervals (95% CI), adjusting for potential confounders. Over a median follow-up of 16 years (IQR: 11-19 years), 6,170 participants were diagnosed with MPC. Having a family history of cancer increased the risk of MPC by 18% (HR, 1.18; 95% CI, 1.12-1.24). A positive linear trend was observed between the reported number of cancers in the family history and MPC risk with HRs (95% CI) of 1.13 (1.07-1.20), 1.23 (1.14-1.33), 1.29 (1.15-1.45), and 1.42 (1.20-1.70) for one, two, three, and four or more cancers among first-degree relatives, respectively (Ptrend = 2.36 × 10-13). No significant differences were observed by cancer histology or specific cancer types reported in the family history. Our study demonstrates that the family history of cancer is an important risk factor for the development of MPCs and that a comprehensive assessment of the number of cancers reported among first-degree relatives may identify those at higher risk who may benefit from targeted cancer prevention and screening strategies. Prevention Relevance: Our study makes a substantial contribution to the understanding of risk factors for MPCs in the general population. It demonstrates that individuals with a strong family history of cancer are at higher risk for MPCs and may benefit from more targeted cancer prevention and screening interventions.

The Current Status and Prospects of Early Diagnosis and Treatment of Esophageal Cancer in China

The Current Status and Prospects of Early Diagnosis and Treatment of Esophageal Cancer in China

Quantum Dots as a Potential Multifunctional Material for the Enhancement of Clinical Diagnosis Strategies and Cancer Treatments.

Quantum dots (QDs) represent a class of nanoscale wide bandgap semiconductors, and are primarily composed of metals, lipids, or polymers. Their unique electronic and optical properties, which stem from their wide bandgap characteristics, offer significant advantages for early cancer detection and treatment. Metal QDs have already demonstrated therapeutic potential in early tumor imaging and therapy. However, biological toxicity has led to the development of various non-functionalized QDs, such as carbon QDs (CQDs), graphene QDs (GQDs), black phosphorus QDs (BPQDs) and perovskite quantum dots (PQDs). To meet the diverse needs of clinical cancer treatment, functionalized QDs with an array of modifications (lipid, protein, organic, and inorganic) have been further developed. These advancements combine the unique material properties of QDs with the targeted capabilities of biological therapy to effectively kill tumors through photodynamic therapy, chemotherapy, immunotherapy, and other means. In addition to tumor-specific therapy, the fluorescence quantum yield of QDs has gradually increased with technological progress, enabling their significant application in both in vivo and in vitro imaging. This review delves into the role of QDs in the development and improvement of clinical cancer treatments, emphasizing their wide bandgap semiconductor properties.

Peripheral CD8+PD-1+ T cells as novel biomarker for neoadjuvant chemoimmunotherapy in humanized mice of non-small cell lung cancer

Neoadjuvant immunotherapy has shown promising clinical activity in the treatment of early non-small cell lung cancer (NSCLC); however, further clarification of the specific mechanism and identification of biomarkers are imperative prior to implementing it as a daily practice. The study investigated the reprogramming of T cells in both tumor and peripheral blood following neoadjuvant chemoimmunotherapy in a preclinical NSCLC mouse model engrafted with a human immune system. Samples were also collected from 21 NSCLC patients (Stage IA-IIIB) who received neoadjuvant chemoimmunotherapy, and the dynamics of potential biomarkers within these samples were measured and further subjected to correlation analysis with prognosis. Further, we initially investigated the sources of the potential biomarkers. We observed in the humanized mouse model, neoadjuvant chemoimmunotherapy could prevent postoperative recurrence and metastasis by increasing the frequency and cytotoxicity of CD8+ T cells in both peripheral blood (p<0.001) and tumor immune microenvironment (TIME)(p<0.001). The kinetics of peripheral CD8+PD-1+ T cells reflected the changes in the TIME and pathological responses, ultimately predicting survival outcome of mice. In the clinical cohort, patients exhibiting an increase in these T cells post-treatment had a higher rate of complete or major pathological response (p<0.05) and increased immune infiltration (p=0.0012, r=0.792). We identified these T cells originating from tumor draining lymph nodes and subsequently entering the TIME. In conclusion, the kinetics of peripheral CD8+PD-1+ T cells can serve as a predictor for changes in TIME and optimal timing for surgery, ultimately reflecting the outcomes of neoadjuvant chemoimmunotherapy in both preclinical and clinical setting.

Ω-Shaped fiber optic LSPR coated with hybridized nanolayers for tumor cell sensing and photothermal treatment

Circulating tumor cell (CTC) in the blood is the main cause of cancer metastasis for death in cancer patients. It is extremely important for cancer diagnosis at an early stage and treatment to simultaneously detect and kill the CTCs. In this work, a new hybridized nanolayer, namely gold nanoparticle/gold nanorods@ Polydopamine (AuNPs/AuNRs@PDA), was coated on the Ω-shaped fiber optics (Ω-FO) for localized surface plasmonic resonance (LSPR) to perform tumor cell sensing and photothermal treatment (PTT). The PDA nanolayer was formed on a bare fiber optic through the self-polymerization of dopamine under mild conditions. The AuNRs and AuNPs were absorbed on the surface of the PDA nanolayer to form a hybridized nanolayer. The hybridized nanolayer-modified Ω-FO LSPR exhibited a high refractive index sensitivity (RIS) of 37.59 (a.u/RIU) and photothermal conversion efficiency. After being modified with the recognition element of aptamer, the Ω-FO LSPR was used to develop a sensitive and specifical tumor cell sensing. Under the irradiation of near-infrared light (NIR) laser, the Ω-FO LSPR can kill the captured tumor cells with the apoptotic/necrotic rate of 62.6 % and low side-effect for the nontarget cells. The FO LSPR sensor realized the dual functions of CTC sensing and PTT, which provided a new idea for the early diagnosis and treatment of cancer.

Comparison of CT and MRI in the Diagnosis of Liver Tumors: A Retrospective Case-Control Analysis.

To compare the diagnostic value of multi-slice computed tomography (CT) and magnetic resonance imaging (MRI) in liver tumors. Retrospective selection of CT and MRI imaging data from 109 cases of liver tumors treated in our hospital from January 2020 to March 2023. The selection was determined through pathological examination. According to the pathological examination results, 61 cases were benign tumors, and 48 cases were malignant tumors. The hepatic portal flow (HPF), hepatic artery perfusion index (HPI) and hepatic artery perfusion (HAF) of malignant tumors were significantly lower than in benign tumors (P<0.05). The signal enhancement ratio of malignant tumors was significantly higher than in benign tumors, and the peak time was significantly lower than in benign tumors (P<0.05). The sensitivity (97.92%) and accuracy (97.25%) of the combined examination were significantly higher than those of MRI (83.33%, 90.83%) or CT alone (81.25%, 88.99%) (P<0.05). CT and MRI have high application value in the diagnosis and evaluation of liver tumors, and the combination of these two methods can further improve diagnostic sensitivity and accuracy, providing an objective reference for early diagnosis and treatment of liver cancer.</p>.

Analysis of global liver cancer statistics

Liver cancer is a significant contributor to the world's cancer burden. In order to comprehend the variations in its regional, age, gender, and histological subtype distributions as well as its temporal trend, this paper analyzes the worldwide statistical data of liver cancer, including the incidence, mortality, and survival. The findings indicated that the stages of liver cancer control and prevention are heterogeneous among countries and regions. The successful experience of liver cancer control and prevention in some countries should be promoted and disseminated. According to the various national conditions, comprehensive intervention measures, including reducing aflatoxin exposure, promoting vaccination, improving the treatment of chronic hepatitis infection, and implementing early diagnosis and treatment of liver cancer, should be developed.

WSPolyp-SAM: Weakly Supervised and Self-Guided Fine-Tuning of SAM for Colonoscopy Polyp Segmentation

Ensuring precise segmentation of colorectal polyps holds critical importance in the early diagnosis and treatment of colorectal cancer. Nevertheless, existing deep learning-based segmentation methods are fully supervised, requiring extensive, precise, manual pixel-level annotation data, which leads to high annotation costs. Additionally, it remains challenging to train large-scale segmentation models when confronted with limited colonoscopy data. To address these issues, we introduce the general segmentation foundation model—the Segment Anything Model (SAM)—into the field of medical image segmentation. Fine-tuning the foundation model is an effective approach to tackle sample scarcity. However, current SAM fine-tuning techniques still rely on precise annotations. To overcome this limitation, we propose WSPolyp-SAM, a novel weakly supervised approach for colonoscopy polyp segmentation. WSPolyp-SAM utilizes weak annotations to guide SAM in generating segmentation masks, which are then treated as pseudo-labels to guide the fine-tuning of SAM, thereby reducing the dependence on precise annotation data. To improve the reliability and accuracy of pseudo-labels, we have designed a series of enhancement strategies to improve the quality of pseudo-labels and mitigate the negative impact of low-quality pseudo-labels. Experimental results on five medical image datasets demonstrate that WSPolyp-SAM outperforms current fully supervised mainstream polyp segmentation networks on the Kvasir-SEG, ColonDB, CVC-300, and ETIS datasets. Furthermore, by using different amounts of training data in weakly supervised and fully supervised experiments, it is found that weakly supervised fine-tuning can save 70% to 73% of annotation time costs compared to fully supervised fine-tuning. This study provides a new perspective on the combination of weakly supervised learning and SAM models, significantly reducing annotation time and offering insights for further development in the field of colonoscopy polyp segmentation.

An ultrasensitive electrochemical/colorimetric dual-mode self-powered biosensing platform for lung cancer marker detection by multiple-signal amplification strategy

BackgroundIn recent years, miRNAs have emerged as potentially valuable tumor markers, and their sensitive and accurate detection is crucial for early screening and diagnosis of tumors. However, the analysis of miRNAs faces significant challenges due to their short sequence, susceptibility to degradation, high similarity, low expression level in cells, and stringent requirements for in vitro research environments. Therefore, the development of sensitive and efficient new methods for the detection of tumor markers is crucial for the early intervention of related tumors. ResultsAn ultrasensitive electrochemical/colorimetric dual-mode self-powered biosensor platform is established to detect microRNA-21 (miR-21) via a multi-signal amplification strategy. Gold nanoparticles (AuNPs) and VS4 nanosheets self-assembled 3D nanorods (VS4-Ns-Nrs) are prepared for constructing a superior performance enzyme biofuel cell (EBFC). The double-signal amplification strategy of Y-shaped DNA nanostructure and catalytic hairpin assembly (CHA) is adopted to further improve enhance the strength and specificity of the output signal. In addition, a capacitor is matched with EBFC to generate an instantaneous current that is amplified several times, and the output detection signal is improved once more. At the same time, electrochemical and colorimetric methods are used for dual-mode strategy to achieve the accuracy of detection. The linear range of detection is from 0.001 pg/mL to 1000 pg/mL, with a relatively low limit of detection (LOD) of 0.16 fg/mL (S/N = 3). SignificanceThe established method enables accurate and sensitive detection of markers in patients with lung cancer, providing technical support and data reference for precise identification. It is anticipated to offer a sensitive and practical new technology and approach for early diagnosis, clinical treatment, and drug screening of cancer and other related major diseases.

γ-Glutamyltranspeptidase fluorescence lifetime response probe for precision tumor detection unveiling A549 cancer cell specificity

γ-Glutamyltranspeptidase (γ-GGT), as a key enzyme, exhibits markedly higher expression levels in tumor cells compared to normal cells. Under normal conditions, γ-GGT activity on the cell membrane is relatively low, but it undergoes a significant upregulation in cancer cells, making it a potential cancer biomarker. Particularly in A549 cells, a prominent cancer cell line, the pronounced upregulation of γ-GGT expression emphasizes its potential as a unique recognition target and a robust marker for A549 cells. This study successfully synthesized a highly selective γ-GGT fluorescent probe, the exhibits commendable sensitivity (LOD = 0.0021U/mL) and selectivity, achieving efficient detection at the cellular level and providing accurate insights into differential expression between normal and cancer cells. The alterations in fluorescence lifetime observed before and after the probe's reaction with γ-GGT serve as a crucial foundation for fluorescence lifetime imaging on living cells. The probe has become a powerful tool for precise localization of tumor cells, particularly demonstrating its capability for specific recognition in A549 cells. Overall, this research highlights the potential of γ-GGT as a target for fluorescent probes, emphasizing its prospects in specific recognition, particularly in A549 cells, with profound implications for advancing early cancer diagnosis and treatment methods.

EfficientSkinSegNet: a lightweight convolutional neural network for accurate skin lesion segmentation

Accurate segmentation of skin lesions is crucial for the early detection and treatment of skin cancer. In this study, we propose EfficientSkinSegNet, a novel lightweight convolutional neural network architecture specifically designed for precise skin lesion segmentation. EfficientSkinSegNet incorporates efficient feature extraction encoders and decoders, leveraging multi-head convolutional attention and spatial channel attention mechanisms to extract and enhance informative features while eliminating redundant ones. Furthermore, a multi-scale feature fusion module is introduced in the skip connections to facilitate effective fusion of features at different scales. Experimental evaluations on benchmark datasets demonstrate that EfficientSkinSegNet outperforms state-of-the-art methods in terms of segmentation accuracy while maintaining a compact model size. The proposed network shows promise for practical clinical diagnostic applications, providing a balance between segmentation performance and computational efficiency. Future research will focus on evaluating EfficientSkinSegNet’s performance on diverse semantic segmentation tasks and optimizing it for medical image analysis.

The oncogenic roles of GPR176 in ovarian cancer: a molecular target for aggressiveness and gene therapy

Background At present, the discovery of new biomarkers is of great significance for the early diagnosis, treatment and prognosis assessment of ovarian cancer. Previous findings indicated that aberrant G-protein-coupled receptor 176 (GPR176) expression might contribute to tumorigenesis and subsequent progression. However, the expression of GPR176 and the molecular mechanisms in ovarian cancer had not been investigated. Methods GPR176 expression was compared with clinicopathological features of ovarian cancer using immunohistochemical and bioinformatics analyses. GPR176-related genes and pathways were analysed using bioinformatics analysis. Additionally, the effects of GPR176 on ovarian cancer cell phenotypes were investigated. Results GPR176 expression positively correlated with elder age, clinicopathological staging, tumour residual status, and unfavourable survival of ovarian cancer, but negatively with purity loss, infiltration of B cells, and CD8+ T cells. Gene Set Enrichment Analysis showed that differential expression of GPR176 was involved in focal adhesion, ECM-receptor interaction, cell adhesion molecules and so on. STRING and Cytoscape were used to determine the top 10 nodes. Kyoto Encyclopaedia of Genes and Genomes analysis indicated that GPR176-related genes were involved in the ECM structural constituent and organisation and so on. GPR176 overexpression promoted the proliferation, anti-apoptosis, anti-pyroptosis, migration and invasion of ovarian cancer cells with overexpression of N-cadherin, Zeb1, Snail, Twist1, and under-expression of gasdermin D, caspase 1, and E-cadherin. Conclusion GPR176 might be involved in the progression of ovarian cancer. It might be used as a biomarker to indicate the aggressive behaviour and poor prognosis of ovarian cancer and a target of genetic therapy.