Deep-learning-based 3D super-resolution CT radiomics model: Predict the possibility of the micropapillary/solid component of lung adenocarcinoma.

Objective: Invasive lung adenocarcinoma（ILA） with micropapillary (MPP)/solid (SOL) components has a poor prognosis. Preoperative identification is essential for decision-making for subsequent treatment. This study aims to construct and evaluate a super-resolution（SR） enhanced radiomics model designed to predict the presence of MPP/SOL components preoperatively to provide more accurate and individualized treatment planning. Methods: Between March 2018 and November 2023, patients who underwent curative intent ILA resection were included in the study. We implemented a deep transfer learning network on CT images to improve their resolution, resulting in the acquisition of preoperative super-resolution CT (SR-CT) images. Models were developed using radiomic features extracted from CT and SR-CT images. These models employed a range of classifiers, including Logistic Regression (LR), Support Vector Machines (SVM), k-Nearest Neighbors (KNN), Random Forest, Extra Trees, Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Multilayer Perceptron (MLP). The diagnostic performance of the models was assessed by measuring the area under the curve (AUC). Result: A total of 245 patients were recruited, of which 109 (44.5 %) were diagnosed with ILA with MPP/SOL components. In the analysis of CT images, the SVM model exhibited outstanding effectiveness, recording AUC scores of 0.864 in the training group and 0.761 in the testing group. When this SVM approach was used to develop a radiomics model with SR-CT images, it recorded AUCs of 0.904 in the training and 0.819 in the test cohorts. The calibration curves indicated a high goodness of fit, while decision curve analysis (DCA) highlighted the model's clinical utility. Conclusion: The study successfully constructed and evaluated a deep learning（DL）-enhanced SR-CT radiomics model. This model outperformed conventional CT radiomics models in predicting MPP/SOL patterns in ILA. Continued research and broader validation are necessary to fully harness and refine the clinical potential of radiomics when combined with SR reconstruction technology.

A combination of radiomic features, clinic characteristics, and serum tumor biomarkers to predict the possibility of the micropapillary/solid component of lung adenocarcinoma.

BACKGROUND: Invasive lung adenocarcinoma with MPP/SOL components has a poor prognosis and often shows a tendency to recurrence and metastasis. This poor prognosis may require adjustment of treatment strategies. Preoperative identification is essential for decision-making for subsequent treatment. OBJECTIVE: This study aimed to preoperatively predict the probability of MPP/SOL components in lung adenocarcinomas by a comprehensive model that includes radiomics features, clinical characteristics, and serum tumor biomarkers. DESIGN: A retrospective case control, diagnostic accuracy study. METHODS: This study retrospectively recruited 273 patients (males: females, 130: 143; mean age ± standard deviation, 63.29 ± 10.03 years; range 21-83 years) who underwent resection of invasive lung adenocarcinoma. Sixty-one patients (22.3%) were diagnosed with lung adenocarcinoma with MPP/SOL components. Radiomic features were extracted from CT before surgery. Clinical, radiomic, and combined models were developed using the logistic regression algorithm. The clinical and radiomic signatures were integrated into a nomogram. The diagnostic performance of the models was evaluated using the area under the curve (AUC). Studies were scored according to the Radiomics Quality Score and Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis guidelines. RESULTS: The radiomics model achieved the best AUC values of 0.858 and 0.822 in the training and test cohort, respectively. Tumor size (T_size), solid tumor size (ST_size), consolidation-to-tumor ratio (CTR), years of smoking, CYFRA 21-1, and squamous cell carcinoma antigen were used to construct the clinical model. The clinical model achieved AUC values of 0.741 and 0.705 in the training and test cohort, respectively. The nomogram showed higher AUCs of 0.894 and 0.843 in the training and test cohort, respectively. CONCLUSION: This study has developed and validated a combined nomogram, a visual tool that integrates CT radiomics features with clinical indicators and serum tumor biomarkers. This innovative model facilitates the differentiation of micropapillary or solid components within lung adenocarcinoma and achieves a higher AUC, indicating superior predictive accuracy.

A new tool to predict aggressive lung cancer types before surgeryWe developed a tool to help doctors determine whether lung cancer is one of the more dangerous types, called micropapillary (MPP) or solid (SOL) patterns, before surgery. These patterns can be more harmful and spread quickly, so knowing they are there can help doctors plan the best treatment. We looked at the cases of 273 lung cancer patients who had surgery and found that 61 of them had these aggressive cancer types. To predict these patterns, we used a computer process known as logistic regression, analyzing CT scan details, health information, and blood tests for cancer markers. Based on CT scans, our tool was very good at predicting whether these patterns were present in two patient groups. However, predictions using only basic health information like the size of the tumor and whether the patient smoked needed to be more accurate. We found a way to make our predictions even better. Combining all information into one chart, known as a nomogram, significantly improved our ability to predict these dangerous cancer patterns. This combined chart could be a big help for doctors. It gives them a clearer picture of the cancer's aggressiveness before surgery, which can guide them to choose the best treatment options. This approach aims to offer a better understanding of the tumor, leading to more tailored and effective treatments for patients facing lung cancer.

Potential Effects of Traditional Chinese Medicine in Anti-Aging and Aging-Related Diseases: Current Evidence and Perspectives.

Aging and aging-related diseases present a global public health problem. Therefore, the development of efficient anti-aging drugs has become an important area of research. Traditional Chinese medicine is an important complementary and alternative branch of aging-related diseases therapy. Recently, a growing number of studies have revealed that traditional Chinese medicine has a certain delaying effect on the progression of aging and aging-related diseases. Here, we review the progress in research into using traditional Chinese medicine for aging and aging-related diseases (including neurodegenerative diseases, cardiovascular diseases, diabetes, and cancer). Furthermore, we summarize the potential mechanisms of action of traditional Chinese medicine and provide references for further studies on aging and aging-related diseases.

Identification of naphthalimide-derivatives as novel PBD-targeted polo-like kinase 1 inhibitors with efficacy in drug-resistant lung cancer cells.

Targeting polo-box domain (PBD) small molecule for polo-like kinase 1 (PLK1) inhibition is a viable alternative to target kinase domain (KD), which could avoid pan-selectivity and dose-limiting toxicity of ATP-competitive inhibitors. However, their efficacy in these settings is still low and inaccessible to clinical requirement. Herein, we utilized a structure-based high-throughput virtual screen to find novel chemical scaffold capable of inhibiting PLK1 via targeting PBD and identified an initial hit molecule compound 1a. Based on the lead compound 1a, a structural optimization approach was carried out and several series of derivatives with naphthalimide structural motif were synthesized. Compound 4Bb was identified as a new potent PLK1 inhibitor with a KD value of 0.29 µM. 4Bb could target PLK1 PBD to inhibit PLK1 activity and subsequently suppress the interaction of PLK1 with protein regulator of cytokinesis 1 (PRC1), finally leading to mitotic catastrophe in drug-resistant lung cancer cells. Furthermore, 4Bb could undergo nucleophilic substitution with the thiol group of glutathione (GSH) to disturb the redox homeostasis through exhausting GSH. By regulating cell cycle machinery and increasing cellular oxidative stress, 4Bb exhibited potent cytotoxicity to multiple cancer cells and drug-resistant cancer cells. Subcutaneous and oral administration of 4Bb could effectively inhibit the growth of drug-resistant tumors in vivo, doubling the survival time of tumor bearing mice without side effects in normal tissues. Thus, our study offers an orally-available, structurally-novel PLK1 inhibitor for drug-resistant lung cancer therapy.

Post-translational protein lactylation modification in health and diseases: a double-edged sword.

As more is learned about lactate, it acts as both a product and a substrate and functions as a shuttle system between different cell populations to provide the energy for sustaining tumor growth and proliferation. Recent discoveries of protein lactylation modification mediated by lactate play an increasingly significant role in human health (e.g., neural and osteogenic differentiation and maturation) and diseases (e.g., tumors, fibrosis and inflammation, etc.). These views are critically significant and first described in detail in this review. Hence, here, we focused on a new target, protein lactylation, which may be a "double-edged sword" of human health and diseases. The main purpose of this review was to describe how protein lactylation acts in multiple physiological and pathological processes and their potential mechanisms through an in-depth summary of preclinical in vitro and in vivo studies. Our work aims to provide new ideas for treating different diseases and accelerate translation from bench to bedside.

The efficacy and safety of fexuprazan in treating erosive esophagitis: a phase III, randomized, double-blind, multicenter study.

BACKGROUND AND AIM: Fexuprazan is a novel potassium-competitive acid blocker (P-CAB). This study aimed to explore the noninferior efficacy and safety of fexuprazan to esomeprazole in treating erosive esophagitis (EE). METHODS: This was a phase III, randomized, double-blind multicenter study. Patients with endoscopically confirmed EE were randomized to receive fexuprazan 40 mg or esomeprazole 40 mg once a daily for 4-8 weeks. The healing rates of EE, symptom response, GERD-health-related quality life (GERD-HRQL), and treatment-emergent adverse events (TEAEs) were compared between fexuprazan group and esomeprazole group. RESULTS: A total of 332 subjects were included in full analysis set (FAS) and 311 in per-protocol set (PPS). The healing rates of fexuprazan and esomeprazole groups at 8 weeks were 88.5% (146/165) and 89.0% (145/163), respectively, in FAS and 97.3% (145/149) and 97.9% (143/146), respectively, in PPS. Noninferiority of fexuprazan compared with esomeprazole according to EE healing rates at 8 weeks was demonstrated in both FAS and PPS analysis. No significant difference was found between groups in EE healing rates at 4 weeks, symptom responses, and changes of GERD-HRQL. The incidence of drug-related AEs was 19.4% (32/165) in fexuprazan arm and 19.6% (32/163) in esomeprazole arm. CONCLUSION: This study demonstrated noninferior efficacy of fexuprazan to esomeprazole in treating EE. The incidence of TEAEs was similar between fexuprazan and esomeprazole. Trial registration number NCT05813561.