Effects of Haskap (Lonicera caerulea L.) Extracts against Oxidative Stress and Inflammation in RAW 264.7 Cells.

This study aimed to evaluate the antioxidant and anti-inflammatory activities of Lonicera caerulea L. ethanol extract (LCEE) and water extract (LCWE) in vitro. We primarily evaluated the improvement effect of LCWE and LCEE on hydrogen peroxide (H2O2)-induced oxidative damage and lipopolysaccharide (LPS)-induced inflammatory damage in RAW 264.7 cells by detecting oxidation-related indicators and inflammatory factors, respectively. Cellular studies showed that LCWE and LCEE increased superoxide dismutase and catalase antioxidant enzyme levels and decreased malondialdehyde and nitric oxide peroxide levels in H2O2-induced RAW 264.7 cells. Moreover, LCWE and LCEE decreased the secretion of inflammatory factors [e.g., interleukin (IL)-6, IL-1ß, and tumor necrosis factor-α] in LPS-induced RAW 264.7 cells. In conclusion, LCWE and LCEE demonstrated excellent antioxidant and anti-inflammatory effects in vitro. However, LCWE was superior to LCEE, which may be related to its chemical composition and requires further research.

A Novel Deep Learning-based Artificial Intelligence System for Interpreting Urolithiasis in Computed Tomography.

BACKGROUND AND OBJECTIVE: Our aim was to develop an artificial intelligence (AI) system for detection of urolithiasis in computed tomography (CT) images using advanced deep learning capable of real-time calculation of stone parameters such as volume and density, which are essential for treatment decisions. The performance of the system was compared to that of urologists in emergency room (ER) scenarios. METHODS: Axial CT images for patients who underwent stone surgery between August 2022 and July 2023 comprised the data set, which was divided into 70% for training, 10% for internal validation, and 20% for testing. Two urologists and an AI specialist annotated stones using Labelimg for ground-truth data. The YOLOv4 architecture was used for training, with acceleration via an RTX 4900 graphics processing unit (GPU). External validation was performed using CT images for 100 patients with suspected urolithiasis. KEY FINDINGS AND LIMITATIONS: The AI system was trained on 39 433 CT images, of which 9.1% were positive. The system achieved accuracy of 95%, peaking with a 1:2 positive-to-negative sample ratio. In a validation set of 5736 images (482 positive), accuracy remained at 95%. Misses (2.6%) were mainly irregular stones. False positives (3.4%) were often due to artifacts or calcifications. External validation using 100 CT images from the ER revealed accuracy of 94%; cases that were missed were mostly ureterovesical junction stones, which were not included in the training set. The AI system surpassed human specialists in speed, analyzing 150 CT images in 13 s, versus 38.6 s for evaluation by urologists and 23 h for formal reading. The AI system calculated stone volume in 0.2 s, versus 77 s for calculation by urologists. CONCLUSIONS AND CLINICAL IMPLICATIONS: Our AI system, which uses advanced deep learning, assists in diagnosing urolithiasis with 94% accuracy in real clinical settings and has potential for rapid diagnosis using standard consumer-grade GPUs. PATIENT SUMMARY: We developed a new AI (artificial intelligence) system that can quickly and accurately detect kidney stones in CT (computed tomography) scans. Testing showed that this system is highly effective, with accuracy of 94% for real cases in the emergency department. It is much faster than traditional methods and provides rapid and reliable results to help doctors in making better treatment decisions for their patients.

Moderation of thyroid hormones for the relationship between amyloid and tau pathology.

BACKGROUND: Altered thyroid hormone levels have been associated with increased risk of Alzheimer's disease (AD) dementia and related cognitive decline. However, the neuropathological substrates underlying the link between thyroid hormones and AD dementia are not yet fully understood. We first investigated the association between serum thyroid hormone levels and in vivo AD pathologies including both beta-amyloid (Aß) and tau deposition measured by positron emission tomography (PET). Given the well-known relationship between Aß and tau pathology in AD, we additionally examined the moderating effects of thyroid hormone levels on the association between Aß and tau deposition. METHODS: This cross-sectional study was conducted as part of the Korean Brain Aging Study for Early Diagnosis and Prediction of Alzheimer's Disease (KBASE) cohort. This study included a total of 291 cognitively normal adults aged 55 to 90. All participants received comprehensive clinical assessments, measurements for serum total triiodothyronine (T3), free triiodothyronine (fT3), free thyroxine (fT4), and thyroid-stimulating hormone (TSH), and brain imaging evaluations including [11C]-Pittsburgh compound B (PiB)- PET and [18F] AV-1451 PET. RESULTS: No associations were found between either thyroid hormones or TSH and Aß and tau deposition on PET. However, fT4 (p = 0.002) and fT3 (p = 0.001) exhibited significant interactions with Aß on tau deposition: The sensitivity analyses conducted after the removal of an outlier showed that the interaction effect between fT4 and Aß deposition was not significant, whereas the interaction between fT3 and Aß deposition remained significant. However, further subgroup analyses demonstrated a more pronounced positive relationship between Aß and tau in both the higher fT4 and fT3 groups compared to the lower group, irrespective of outlier removal. Meanwhile, neither T3 nor TSH had any interaction with Aß on tau deposition. CONCLUSION: Our findings suggest that serum thyroid hormones may moderate the relationship between cerebral Aß and tau pathology. Higher levels of serum thyroid hormones could potentially accelerate the Aß-dependent tau deposition in the brain. Further replication studies in independent samples are needed to verify the current results.

Image Quality Assessment Using Convolutional Neural Network in Clinical Skin Images.

The image quality received for clinical evaluation is often suboptimal. The goal is to develop an image quality analysis tool to assess patient- and primary care physician-derived images using deep learning model. Dataset included patient- and primary care physician-derived images from August 21, 2018 to June 30, 2022 with 4 unique quality labels. VGG16 model was fine tuned with input data, and optimal threshold was determined by Youden's index. Ordinal labels were transformed to binary labels using a majority vote because model distinguishes between 2 categories (good vs bad). At a threshold of 0.587, area under the curve for the test set was 0.885 (95% confidence interval = 0.838-0.933); sensitivity, specificity, positive predictive value, and negative predictive value were 0.829, 0.784, 0.906, and 0.645, respectively. Independent validation of 300 additional images (from patients and primary care physicians) demonstrated area under the curve of 0.864 (95% confidence interval = 0.818-0.909) and area under the curve of 0.902 (95% confidence interval = 0.85-0.95), respectively. The sensitivity, specificity, positive predictive value, and negative predictive value for the 300 images were 0.827, 0.800, 0.959, and 0.450, respectively. We demonstrate a practical approach improving the image quality for clinical workflow. Although users may have to capture additional images, this is offset by the improved workload and efficiency for clinical teams.

Primary Metabolic Response of Aristolochia contorta to Simulated Specialist Herbivory under Elevated CO2 Conditions.

This study explores how elevated carbon dioxide (CO2) levels affects the growth and defense mechanisms of plants. We focused on Aristolochia contorta Bunge (Aristolochiaceae), a wild plant that exhibits growth reduction under elevated CO2 in the previous study. The plant has Sericinus montela Gray (Papilionidae) as a specialist herbivore. By analyzing primary metabolites, understanding both the growth and defense response of plants to herbivory under elevated CO2 conditions is possible. The experiment was conducted across four groups, combining two CO2 concentration conditions (ambient CO2 and elevated CO2) with two herbivory conditions (herbivory treated and untreated). Although many plants exhibit increased growth under elevated CO2 levels, A. contorta exhibited reduced growth with lower height, dry weight, and total leaf area. Under herbivory, A. contorta triggered both localized and systemic responses. More primary metabolites exhibited significant differences due to herbivory treatment in systemic tissue than local leaves that herbivory was directly treated. Herbivory under elevated CO2 level triggered more significant responses in primary metabolites (17 metabolites) than herbivory under ambient CO2 conditions (five metabolites). Several defense-related metabolites exhibited higher concentrations in the roots and lower concentrations in the leaves in response to the herbivory treatment in the elevated CO2 group. This suggests a potential intensification of defensive responses in the underground parts of the plant under elevated CO2 levels. Our findings underscore the importance of considering both abiotic and biotic factors in understanding plant responses to environmental changes. The adaptive strategies of A. contorta suggest a complex response mechanism to elevated CO2 and herbivory pressures.

Exploring the Regulatory Landscape of Dementia: Insights from Non-Coding RNAs.

Dementia, a multifaceted neurological syndrome characterized by cognitive decline, poses significant challenges to daily functioning. The main causes of dementia, including Alzheimer's disease (AD), frontotemporal dementia (FTD), Lewy body dementia (LBD), and vascular dementia (VD), have different symptoms and etiologies. Genetic regulators, specifically non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs), are known to play important roles in dementia pathogenesis. MiRNAs, small non-coding RNAs, regulate gene expression by binding to the 3' untranslated regions of target messenger RNAs (mRNAs), while lncRNAs and circRNAs act as molecular sponges for miRNAs, thereby regulating gene expression. The emerging concept of competing endogenous RNA (ceRNA) interactions, involving lncRNAs and circRNAs as competitors for miRNA binding, has gained attention as potential biomarkers and therapeutic targets in dementia-related disorders. This review explores the regulatory roles of ncRNAs, particularly miRNAs, and the intricate dynamics of ceRNA interactions, providing insights into dementia pathogenesis and potential therapeutic avenues.

Improvements in Resistive and Capacitive Switching Behaviors in Ga2O3 Memristors via High-Temperature Annealing Process.

This study investigates the effect of a high-temperature annealing process on the characteristics and performance of a memristor based on a Ag/Ga2O3/Pt structure. Through X-ray diffraction analysis, successful phase conversion from amorphous Ga2O3 to ß-Ga2O3 is confirmed, attributed to an increase in grain size and recrystallization induced by annealing. X-ray photoelectron spectroscopy analysis revealed a higher oxygen vacancy in annealed Ga2O3 thin films, which is crucial for conductive filament formation and charge transport in memristors. Films with abundant oxygen vacancies exhibit decreased set voltages and increased capacitance in a low-resistive state, enabling easy capacitance control depending on channel presence. In addition, an excellent memory device with a high on/off ratio can be implemented due to the reduction of leakage current due to recrystallization. Therefore, it is possible to manufacture a thin film suitable for a memristor by increasing the oxygen vacancy in the Ga2O3 film while improving the overall crystallinity through the annealing process. This study highlights the significance of annealing in modulating capacitance and high-resistive/low-resistive state properties of Ga2O3 memristors, contributing to optimizing device design and performance. This study underscores the significance of high-temperature annealing in improving the channel-switching characteristics of Ga2O3-based memristors, which is crucial for the development of low-power, high-efficiency memory device.

Clinical Importance of Grading Tumor Spread through Air Spaces in Early-Stage Small-Lung Adenocarcinoma.

This study aimed to identify the clinical manifestation and implications according to the grading of tumor spread through air spaces in early-stage small (≤2 cm) pathological stage I non-mucinous lung adenocarcinomas. Medical records of patients with pathological stage I tumors sized ≤2 cm were retrospectively reviewed and analyzed. The furthest distance of the spread through air spaces from the tumor margin was measured on a standard-length scale (mm). Enrolled patients were categorized into spread through air spaces (STAS) (-) and STAS (+), and STAS (+) was subdivided according to its furthest distance as follows: STAS (+)-L (<2 mm) and STAS (+)-H (≥2 mm). Risk factors for STAS (+) included papillary predominant subtype (p = 0.027), presence of micropapillary patterns (p < 0.001), and EGFR (p = 0.039). The overall survival of the three groups did not differ significantly (p = 0.565). The recurrence-free survival of STAS (+)-H groups was significantly lower than those of STAS (-) and STAS (+)-L (p < 0.001 and p = 0.039, respectively). A number of alveolar spaces were definite risk factors for STAS (+)-H groups (p < 0.001), and male gender could be one (p = 0.054). In the patient group with small (≤2 cm) pathological stage I lung adenocarcinomas, the presence of STAS ≥ 2 mm was related to significantly lower recurrence-free survival. For identifying definite risk factors for the presence of farther STAS, more precise analysis from a larger study population should be undertaken.

Modulation of macrophage transcript and secretion profiles by Sargassum Serratifolium extract is associated with the suppression of muscle atrophy.

Recent research has emphasized the role of macrophage-secreted factors on skeletal muscle metabolism. We studied Sargassum Serratifolium ethanol extract (ESS) in countering lipopolysaccharide (LPS)-induced changes in the macrophage transcriptome and their impact on skeletal muscle. Macrophage-conditioned medium (MCM) from LPS-treated macrophages (LPS-MCM) and ESS-treated macrophages (ESS-MCM) affected C2C12 myotube cells. LPS-MCM upregulated muscle atrophy genes and reduced glucose uptake, while ESS-MCM reversed these effects. RNA sequencing revealed changes in the immune system and cytokine transport pathways in ESS-treated macrophages. Protein analysis in ESS-MCM showed reduced levels of key muscle atrophy-related proteins, TNF-α, IL-6, IL-1, and GDF-15. These proteins play crucial roles in muscle function. These findings highlight the intricate relationship between the macrophage transcriptome and their secreted factors in either impairing or enhancing skeletal muscle function. ESS treatment has the potential to reduce macrophage-derived cytokines, preserving skeletal muscle function.

Anti-cancer effects of benzimidazole derivative BNZ-111 on paclitaxel-resistant ovarian cancer.

OBJECTIVE: Ovarian cancer, a leading cause of cancer-related deaths in women, remains a formidable challenge, especially in the context of platinum-resistant disease. This study investigated the potential of the benzimidazole derivative BNZ-111 as a novel treatment strategy for platinum-resistant ovarian cancer. METHODS: The human EOC cell lines A2780, HeyA8, SKOV3ip1, A2780-CP20, HeyA8-MDR, and SKOV3-TR were treated with BNZ-111, and cell proliferation, apoptosis, and cell cycle were assessed. RESULTS: It demonstrated strong cytotoxicity in both chemo-sensitive and chemo-resistant epithelial ovarian cancer cell lines, inducing apoptosis and G2/M cell cycle arrest. In vivo experiments using orthotopic and patient-derived xenograft models showed significant tumor growth inhibition without apparent toxicity to vital organs. Unlike paclitaxel, BNZ-111 proved effective in paclitaxel-resistant cells, potentially by bypassing interaction with MDR1 and modulating ß-3 tubulin expression to suppress microtubule dynamics. CONCLUSION: BNZ-111, with favorable drug-like properties, holds promise as a therapeutic option for platinum-resistant ovarian cancer, addressing a critical clinical need in gynecologic oncology.

The beneficial effects of ethanolic extract of Sargassum serratifolium in DNCB-induced mouse model of atopic dermatitis.

Atopic dermatitis is a chronic complex inflammatory skin disorder that requires sustainable treatment methods due to the limited efficacy of conventional therapies. Sargassum serratifolium, an algal species with diverse bioactive substances, is investigated in this study for its potential benefits as a therapeutic agent for atopic dermatitis. RNA sequencing of LPS-stimulated macrophages treated with ethanolic extract of Sargassum serratifolium (ESS) revealed its ability to inhibit a broad range of inflammation-related signaling, which was proven in RAW 264.7 and HaCaT cells. In DNCB-induced BALB/c or HR-1 mice, ESS treatment improved symptoms of atopic dermatitis within the skin, along with histological improvements such as reduced epidermal thickness and infiltration of mast cells. ESS showed a tendency to improve serum IgE levels and inflammation-related cytokine changes, while also improving the mRNA expression levels of Chi3l3, Ccr1, and Fcεr1a genes in the skin. Additionally, ESS compounds (sargachromanol (SCM), sargaquinoic acid (SQA), and sargahydroquinoic acid (SHQA)) mitigated inflammatory responses in LPS-treated RAW264.7 macrophages. In summary, ESS has an anti-inflammatory effect and improves atopic dermatitis, ESS may be applied as a therapeutics for atopic dermatitis.

Factors Considered by Experienced Urologists when Selecting Alpha-Blockers for Patients with Lower Urinary Tract Symptoms or Benign Prostatic Hyperplasia according to Age.

INTRODUCTION: The objectives of the study were to examine the opinions of urology specialists on whether there are actual differences in efficacy among α1-blockers and to identify the factors that should be considered when prescribing these medications according to age. METHODS: We surveyed 50 South Korean urology specialists with over 3 years of clinical experience in secondary or tertiary hospitals in July-August 2021. The survey covered urologists' demographics, awareness of α1-blocker prescription differences, and key factors in α1-blocker selection based on LUTS severity and patient age. RESULTS: Overall, 82% of the respondents believed that there were differences in the efficacy of α1-blockers in actual practice according to age. Over 90% of the respondents agreed on the need for head-to-head comparison studies to compare the effects of different α1-blockers. Regardless of the severity of LUTS, urologists prioritize cardiovascular side effects when prescribing α1-blockers to patients aged ≥70 years. Further, 19% of the urologists prioritized ejaculatory side effects for mild-to-moderate LUTS and 9% for severe LUTS (p < 0.001). CONCLUSIONS: This study shows that head-to-head studies comparing the efficacy of different α1-blockers are highly valuable for the real-world clinical application of α1-blockers. Notably, urologists prioritize cardiovascular and ejaculatory side effects in older and younger patients while prescribing α1-blockers, respectively.

Evaluation of Drug Blood-Brain-Barrier Permeability Using a Microfluidic Chip.

The blood-brain-barrier (BBB) is made up of blood vessels whose permeability enables the passage of some compounds. A predictive model of BBB permeability is important in the early stages of drug development. The predicted BBB permeabilities of drugs have been confirmed using a variety of in vitro methods to reduce the quantities of drug candidates needed in preclinical and clinical trials. Most prior studies have relied on animal or cell-culture models, which do not fully recapitulate the human BBB. The development of microfluidic models of human-derived BBB cells could address this issue. We analyzed a model for predicting BBB permeability using the Emulate BBB-on-a-chip machine. Ten compounds were evaluated, and their permeabilities were estimated. Our study demonstrated that the permeability trends of ten compounds in our microfluidic-based system resembled those observed in previous animal and cell-based experiments. Furthermore, we established a general correlation between the partition coefficient (Kp) and the apparent permeability (Papp). In conclusion, we introduced a new paradigm for predicting BBB permeability using microfluidic-based systems.

Enhancing Honey Bee Health: Evaluating Pollen Substitute Diets in Field and Cage Experiments.

Honey bees (Apis mellifera L.) play vital roles as agricultural pollinators and honey producers. However, global colony losses are increasing due to multiple stressors, including malnutrition. Our study evaluated the effects of four pollen substitute diets (Diet 1, Diet 2, Diet 3, and Control) through field and cage experiments, analyzing 11 parameters and 21 amino acids. Notably, Diet 1 demonstrated significantly superior performance in the field experiment, including the number of honey bees, brood area, consumption, preference, colony weight, and honey production. In the cage experiment, Diet 1 also showed superior performance in dried head and thorax weight and vitellogenin (vg) gene expression levels. Canonical discriminant and principle component analyses highlighted Diet 1's distinctiveness, with histidine, diet digestibility, consumption, vg gene expression levels, and isoleucine identified as key factors. Arginine showed significant correlations with a wide range of parameters, including the number of honey bees, brood area, and consumption, with Diet 1 exhibiting higher levels. Diet 1, containing apple juice, soytide, and Chlorella as additive components, outperformed the other diets, suggesting an enhanced formulation for pollen substitute diets. These findings hold promise for the development of more effective diets, potentially contributing to honey bee health.

Frequency Domain Deep Learning With Non-Invasive Features for Intraoperative Hypotension Prediction.

BACKGROUND: Intraoperative hypotension can lead to postoperative organ dysfunction. Previous studies primarily used invasive arterial pressure as the key biosignal for the detection of hypotension. However, these studies had limitations in incorporating different biosignal modalities and utilizing the periodic nature of biosignals. To address these limitations, we utilized frequency-domain information, which provides key insights that time-domain analysis cannot provide, as revealed by recent advances in deep learning. With the frequency-domain information, we propose a deep-learning approach that integrates multiple biosignal modalities. METHODS: We used the discrete Fourier transform technique, to extract frequency information from biosignal data, which we then combined with the original time-domain data as input for our deep learning model. To improve the interpretability of our results, we incorporated recent interpretable modules for deep-learning models into our analysis. RESULTS: We constructed 75,994 segments from the data of 3,226 patients to predict hypotension during surgery. Our proposed frequency-domain deep-learning model outperformed conventional approaches that rely solely on time-domain information. Notably, our model achieved a greater increase in AUROC performance than the time-domain deep learning models when trained on non-invasive biosignal data only (AUROC 0.898 [95% CI: 0.885-0.91] vs. 0.853 [95% CI: 0.839-0.867]). Further analysis revealed that the 1.5-3.0 Hz frequency band played an important role in predicting hypotension events. CONCLUSION: Utilizing the frequency domain not only demonstrated high performance on invasive data but also showed significant performance improvement when applied to non-invasive data alone. Our proposed framework offers clinicians a novel perspective for predicting intraoperative hypotension.

Spatial transcriptome analysis of amelanotic acral melanoma reveals distant molecular determinants compared to pigmented acral melanoma.

BACKGROUND: Amelanotic acral melanoma (AAM) is a rare type of acral melanoma associated with poor prognosis. OBJECTIVES: We aimed to investigate the transcriptomic differences between AAM and pigmented acral melanoma (PAM). METHODS: The differences in spatially resolved transcriptome profiles of 9 AAM patients with 29 regions of interest (ROIs) and 11 PAM patients with 46 ROIs were investigated using S100b and CD3 morphology markers. RESULTS: In S100b-positive tumor cell areas, we detected 11 upregulated differentially expressed genes (DEGs), including chaperone/ubiquitin-associated DEGs, and 82 downregulated DEGs, including human leukocyte antigen, in AAMs compared with PAMs. Protein-protein interaction network and pathway analyses revealed significant enrichment of dysregulated translational and nonsense-mediated decay pathways but significant decreases in antigen processing and presentation, interferon signaling, and melanin biosynthesis pathways in S100b-positive ROIs of AAMs compared with those of PAMs. In tumor-associated immune cell areas, the numbers of CD8 T cells (p = 0.044) and M1 macrophages (p = 0.014) were significantly decreased, whereas those of monocytes (p = 0.045) and endothelial cells (p = 0.04) were increased in AAMs compared with those in PAMs. CONCLUSIONS: In conclusion, these findings could widen our understanding of the biological differences between AAMs and PAMs that might result in a different clinical course.

A Finite Element Analysis Study of Edentulous Model with Complete Denture to Simulate Masticatory Movement.

The purposes of this study are to establish and validate a finite element (FE) model using finite element analysis methods and to identify optimal loading conditions to simulate masticatory movement. A three-dimensional FE model of the maxillary and mandibular cortical bone, cancellous bone, and gingiva was constructed based on edentulous cone-beam-computed tomography data. Dental computer-aided design software was used to design the denture base and artificial teeth to produce a complete denture. Mesh convergence was performed to derive the optimal mesh size, and validation was conducted through comparison with mechanical test results. The mandible was rotated step-by-step to induce movements similar to actual mastication. Results showed that there was less than a 6% difference between the mechanical test and the alveolar bone-complete denture. It opened 10° as set in the first stage, confirming that the mouth closed 7° in the second stage. Occlusal contact occurred between the upper and lower artificial teeth as the mouth closed the remaining angle of 3° in the third stage while activating the masseter muscle. These results indicate that the FE model and masticatory loading conditions developed in this study can be applied to analyze biomechanical effects according to the wearing of dentures with various design elements applied.

The Effects of Artificial Diets on the Expression of Molecular Marker Genes Related to Honey Bee Health.

Honey bees are commonly used to study metabolic processes, yet the molecular mechanisms underlying nutrient transformation, particularly proteins and their effects on development, health, and diseases, still evoke varying opinions among researchers. To address this gap, we investigated the digestibility and transformation of water-soluble proteins from four artificial diets in long-lived honey bee populations (Apis mellifera ligustica), alongside their impact on metabolism and DWV relative expression ratio, using transcriptomic and protein quantification methods. Diet 2, characterized by its high protein content and digestibility, was selected for further analysis from the other studied diets. Subsequently, machine learning was employed to identify six diet-related molecular markers: SOD1, Trxr1, defensin2, JHAMT, TOR1, and vg. The expression levels of these markers were found to resemble those of honey bees who were fed with Diet 2 and bee bread, renowned as the best natural food. Notably, honey bees exhibiting chalkbrood symptoms (Control-N) responded differently to the diet, underscoring the unique nutritional effects on health-deficient bees. Additionally, we proposed a molecular model to elucidate the transition of long-lived honey bees from diapause to development, induced by nutrition. These findings carry implications for nutritional research and beekeeping, underscoring the vital role of honey bees in agriculture.

Prognostic Model for High-Grade Neuroendocrine Carcinoma of the Lung Incorporating Genomic Profiling and Poly (ADP-ribose) Polymerase-1 Expression.

PURPOSE: High-grade neuroendocrine carcinoma (HGNEC) of the lung is an aggressive cancer with a complex biology. We aimed to explore the prognostic value of genetic aberrations and poly(ADP-ribose) polymerase-1 (PARP1) expression in HGNEC and to establish a novel prognostic model. MATERIALS AND METHODS: We retrospectively enrolled 191 patients with histologically confirmed HGNEC of the lung. Tumor tissues were analyzed using PARP1 immunohistochemistry (IHC; N = 191) and comprehensive cancer panel sequencing (n = 102). Clinical and genetic data were used to develop an integrated Cox hazards model. RESULTS: Strong PARP1 IHC expression (intensity 3) was observed in 153 of 191 (80.1%) patients, and the mean PARP1 H-score was 285 (range, 5-300). To develop an integrated Cox hazard model, our data set included information from 357 gene mutations and 19 clinical profiles. When the targeted mutation profiles were combined with clinical profiles, 12 genes (ATRX, CCND2, EXT2, FGFR2, FOXO1, IL21R, MAF, TGM7, TNFAIP3, TP53, TSHR, and DDR2) were identified as prognostic factors for survival. The integrated Cox hazard model, which combines mutation profiles with a baseline model, outperformed the baseline model (incremental area under the curve 0.84 v 0.78; P = 8.79e-12). The integrated model stratified patients into high- and low-risk groups with significantly different disease-free and overall survival (integrated model: hazard ratio, 7.14 [95% CI, 4.07 to 12.54]; P < .01; baseline model: 4.38 [2.56 to 7.51]; P < .01). CONCLUSION: We introduced a new prognostic model for HGNEC that combines genetic and clinical data. The integrated Cox hazard model outperformed the baseline model in predicting the survival of patients with HGNEC.

Exploring the Key Signaling Pathways and ncRNAs in Colorectal Cancer.

Colorectal cancer (CRC) is the third most prevalent cancer to be diagnosed, and it has a substantial mortality rate. Despite numerous studies being conducted on CRC, it remains a significant health concern. The disease-free survival rates notably decrease as CRC progresses, emphasizing the urgency for effective diagnostic and therapeutic approaches. CRC development is caused by environmental factors, which mostly lead to the disruption of signaling pathways. Among these pathways, the Wingless/Integrated (Wnt) signaling pathway, Phosphatidylinositol 3-kinase/protein kinase B/mammalian target of rapamycin (PI3K/AKT/mTOR) signaling pathway, Mitogen-Activated Protein Kinase (MAPK) signaling pathway, Transforming Growth Factor-ß (TGF-ß) signaling pathway, and p53 signaling pathway are considered to be important. These signaling pathways are also regulated by non-coding RNAs (ncRNAs), including microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and circular RNAs (circRNAs). They have emerged as crucial regulators of gene expression in CRC by changing their expression levels. The altered expression patterns of these ncRNAs have been implicated in CRC progression and development, suggesting their potential as diagnostic and therapeutic targets. This review provides an overview of the five key signaling pathways and regulation of ncRNAs involved in CRC pathogenesis that are studied to identify promising avenues for diagnosis and treatment strategies.