In situ injectable hydrogel encapsulating Mn/NO-based immune nano-activator for prevention of postoperative tumor recurrence.

Postoperative tumor recurrence remains a predominant cause of treatment failure. In this study, we developed an in situ injectable hydrogel, termed MPB-NO@DOX + ATRA gel, which was locally formed within the tumor resection cavity. The MPB-NO@DOX + ATRA gel was fabricated by mixing a thrombin solution, a fibrinogen solution containing all-trans retinoic acid (ATRA), and a Mn/NO-based immune nano-activator termed MPB-NO@DOX. ATRA promoted the differentiation of cancer stem cells, inhibited cancer cell migration, and affected the polarization of tumor-associated macrophages. The outer MnO2 shell disintegrated due to its reaction with glutathione and hydrogen peroxide in the cytoplasm to release Mn2+ and produce O2, resulting in the release of doxorubicin (DOX). The released DOX entered the nucleus and destroyed DNA, and the fragmented DNA cooperated with Mn2+ to activate the cGAS-STING pathway and stimulate an anti-tumor immune response. In addition, when MPB-NO@DOX was exposed to 808 nm laser irradiation, the Fe-NO bond was broken to release NO, which downregulated the expression of PD-L1 on the surface of tumor cells and reversed the immunosuppressive tumor microenvironment. In conclusion, the MPB-NO@DOX + ATRA gel exhibited excellent anti-tumor efficacy. The results of this study demonstrated the great potential of in situ injectable hydrogels in preventing postoperative tumor recurrence.

CT-based radiomics models predict spontaneous intracerebral hemorrhage expansion and are comparable with CT angiography spot sign.

Background and purpose: This study aimed to investigate the efficacy of radiomics, based on non-contrast computed tomography (NCCT) and computed tomography angiography (CTA) images, in predicting early hematoma expansion (HE) in patients with spontaneous intracerebral hemorrhage (SICH). Additionally, the predictive performance of these models was compared with that of the established CTA spot sign. Materials and methods: A retrospective analysis was conducted using CT images from 182 patients with SICH. Data from the patients were divided into a training set (145 cases) and a testing set (37 cases) using random stratified sampling. Two radiomics models were constructed by combining quantitative features extracted from NCCT images (the NCCT model) and CTA images (the CTA model) using a logistic regression (LR) classifier. Additionally, a univariate LR model based on the CTA spot sign (the spot sign model) was established. The predictive performance of the two radiomics models and the spot sign model was compared according to the area under the receiver operating characteristic (ROC) curve (AUC). Results: For the training set, the AUCs of the NCCT, CTA, and spot sign models were 0.938, 0.904, and 0.726, respectively. Both the NCCT and CTA models demonstrated superior predictive performance compared to the spot sign model (all P < 0.001), with the performance of the two radiomics models being comparable (P = 0.068). For the testing set, the AUCs of the NCCT, CTA, and spot sign models were 0.925, 0.873, and 0.720, respectively, with only the NCCT model exhibiting significantly greater predictive value than the spot sign model (P = 0.041). Conclusion: Radiomics models based on NCCT and CTA images effectively predicted HE in patients with SICH. The predictive performances of the NCCT and CTA models were similar, with the NCCT model outperforming the spot sign model. These findings suggest that this approach has the potential to reduce the need for CTA examinations, thereby reducing radiation exposure and the use of contrast agents in future practice for the purpose of predicting hematoma expansion.

Biosynthetic pathway of prescription cucurbitacin IIa and high-level production of key triterpenoid intermediates in engineered yeast and tobacco.

Cucurbitacin IIa is a triterpenoid isolated exclusively from Hemsleya plants and a non-steroidal anti-inflammatory drug that functions as the main ingredient of prescription Hemslecin capsules and tablets in China. Synthetic biology provides new strategies for production of such valuable cucurbitacins at a large scale; however, the biosynthetic pathway of cucurbitacin IIa has been unknown, and the heterologous production of cucurbitacins in galactose medium has been expensive and low yielding. In this study, we characterized the functions of genes encoding two squalene epoxidases (HcSE1-2), six oxidosqualene cyclases (HcOSC1-6), two CYP450s (HcCYP87D20 and HcCYP81Q59), and an acyltransferase (HcAT1) in cucurbitacin IIa biosynthesis by heterologous expression in Saccharomyces cerevisiae and Nicotiana benthamiana. We achieved high-level production of the key cucurbitacin precursor 11-carbonyl-20ß-hydroxy-Cuol from glucose in yeast via modular engineering of the mevalonate pathway and optimization of P450 expression levels. The resulting yields of 46.41 mg/l 11-carbonyl-20ß-hydroxy-Cuol and 126.47 mg/l total cucurbitacin triterpenoids in shake flasks are the highest yields yet reported from engineered microbes. Subsequently, production of 11-carbonyl-20ß-hydroxy-Cuol by transient gene expression in tobacco resulted in yields of 1.28 mg/g dry weight in leaves. This work reveals the key genes involved in biosynthesis of prescription cucurbitacin IIa and demonstrates that engineered yeast cultivated with glucose can produce high yields of key triterpenoid intermediates. We describe a low-cost and highly efficient platform for rapid screening of candidate genes and high-yield production of pharmacological triterpenoids.

CT-Based Intratumoral and Peritumoral Radiomics Nomograms for the Preoperative Prediction of Spread Through Air Spaces in Clinical Stage IA Non-small Cell Lung Cancer.

The study aims to investigate the value of intratumoral and peritumoral radiomics and clinical-radiological features for predicting spread through air spaces (STAS) in patients with clinical stage IA non-small cell lung cancer (NSCLC). A total of 336 NSCLC patients from our hospital were randomly divided into the training cohort (n = 236) and the internal validation cohort (n = 100) at a ratio of 7:3, and 69 patients from the other two external hospitals were collected as the external validation cohort. Univariate and multivariate analyses were used to select clinical-radiological features and construct a clinical model. The GTV, PTV5, PTV10, PTV15, PTV20, GPTV5, GPTV10, GPTV15, and GPTV20 models were constructed based on intratumoral and peritumoral (5 mm, 10 mm, 15 mm, 20 mm) radiomics features. Additionally, the radscore of the optimal radiomics model and clinical-radiological predictors were used to construct a combined model and plot a nomogram. Lastly, the ROC curve and AUC value were used to evaluate the diagnostic performance of the model. Tumor density type (OR = 6.738) and distal ribbon sign (OR = 5.141) were independent risk factors for the occurrence of STAS. The GPTV10 model outperformed the other radiomics models, and its AUC values were 0.887, 0.876, and 0.868 in the three cohorts. The AUC values of the combined model constructed based on GPTV10 radscore and clinical-radiological predictors were 0.901, 0.875, and 0.878. DeLong test results revealed that the combined model was superior to the clinical model in the three cohorts. The nomogram based on GPTV10 radscore and clinical-radiological features exhibited high predictive efficiency for STAS status in NSCLC.

Prognostic implications of pre-transcatheter aortic valve replacement computed tomography-derived coronary plaque characteristics and stenosis severity.

OBJECTIVES: The study aimed to investigate the prognostic value of pre-transcatheter aortic valve replacement (TAVR) computed tomography angiography (CTA) in assessing physiological stenosis severity (CTA-derived fractional flow reserve (CT-FFR)) and high-risk plaque characteristics (HRPC). MATERIALS AND METHODS: Among TAVR patients who underwent pre-procedure CTA, the presence and number of HRPCs (minimum lumen area of < 4 mm2, plaque burden ≥ 70%, low-attenuating plaques, positive remodeling, napkin-ring sign, or spotty calcification) as well as CT-FFR were assessed. The risk of vessel-oriented composite outcome (VOCO, a composite of vessel-related ischemia-driven revascularization, vessel-related myocardial infarction, or cardiac death) was compared according to the number of HRPC and CT-FFR categories. RESULTS: Four hundred and twenty-seven patients (68.4% were male) with 1072 vessels were included. Their mean age was 70.6 ± 10.6 years. Vessels with low CT-FFR (≤ 0.80) (41.7% vs. 15.8%, adjusted hazard ratio (HRadj) 1.96; 95% confidence interval (CI): 1.28-2.96; p = 0.001) or lesions with ≥ 3 HRPC (38.7% vs. 16.0%, HRadj 1.81; 95%CI 1.20-2.71; p = 0.005) demonstrated higher VOCO risk. In the CT-FFR (> 0.80) group, lesions with ≥ 3 HRPC showed a significantly higher risk of VOCO than those with < 3 HRPC (34.7% vs. 13.0%; HRadj 2.04; 95%CI 1.18-3.52; p = 0.011). However, this relative increase in risk was not observed in vessels with positive CT-FFR (≤ 0.80). CONCLUSIONS: In TAVR candidates, both CT-FFR and the presence of ≥ 3 HRPC were associated with an increased risk of adverse clinical events. However, the value of HRPC differed with the CT-FFR category, with more incremental predictability among vessels with negative CT-FFR but not among vessels with positive CT-FFR. CLINICAL RELEVANCE STATEMENT: In transcatheter aortic valve replacement (TAVR) candidates, pre-TAVR CTA provided the opportunity to assess coronary physiological stenosis severity and high-risk plaque characteristics, both of which are associated with worse clinical outcomes. KEY POINTS: • The current study investigated the prognostic value of coronary physiology significance and plaque characteristics in transcatheter aortic valve replacement patients. • The combination of coronary plaque vulnerability and physiological significance showed improved accuracy in predicting clinical outcomes in transcatheter aortic valve replacement patients. • Pre-transcatheter aortic valve replacement CT can be a one-stop-shop tool for coronary assessments in clinical practice.

Genome-wide identification and expression analysis of the C2H2-zinc finger transcription factor gene family and screening of candidate genes involved in floral development in Coptis teeta Wall. (Ranunculaceae).

Background: C2H2-zinc finger transcription factors comprise one of the largest and most diverse gene superfamilies and are involved in the transcriptional regulation of flowering. Although a large number of C2H2 zinc-finger proteins (C2H2-ZFPs) have been well characterized in a number of model plant species, little is known about their expression and function in Coptis teeta. C. teeta displays two floral phenotypes (herkogamy phenotypes). It has been proposed that the C2H2-zinc finger transcription factor family may play a crucial role in the formation of floral development and herkogamy observed in C. teeta. As such, we performed a genome-wide analysis of the C2H2-ZFP gene family in C. teeta. Results: The complexity and diversity of C. teeta C2H2 zinc finger proteins were established by evaluation of their physicochemical properties, phylogenetic relationships, exon-intron structure, and conserved motifs. Chromosome localization showed that 95 members of the C2H2 zinc-finger genes were unevenly distributed across the nine chromosomes of C. teeta, and that these genes were replicated in tandem and segmentally and had undergone purifying selection. Analysis of cis-acting regulatory elements revealed a possible involvement of C2H2 zinc-finger proteins in the regulation of phytohormones. Transcriptome data was then used to compare the expression levels of these genes during the growth and development of the two floral phenotypes (F-type and M-type). These data demonstrate that in groups A and B, the expression levels of 23 genes were higher in F-type flowers, while 15 genes showed higher expressions in M-type flowers. qRT-PCR analysis further revealed that the relative expression was highly consistent with the transcriptome data. Conclusion: These data provide a solid basis for further in-depth studies of the C2H2 zinc finger transcription factor gene family in this species and provide preliminary information on which to base further research into the role of the C2H2 ZFPs gene family in floral development in C. teeta.

Sex Differences in Coronary Inflammation and Atherosclerosis Phenotypes in Response to Imaging Marker of Stress-Related Neural Activity.

BACKGROUND: Sex-specific differences in coronary phenotypes in response to stress have not been elucidated. This study investigated the sex-specific differences in the coronary computed tomography angiography-assessed coronary response to mental stress. METHODS: This retrospective study included patients with coronary artery disease and without cancer who underwent resting 18F-fluorodexoyglucose positron emission tomography/computed tomography and coronary computed tomography angiography within 3 months. 18F-flourodeoxyglucose resting amygdalar uptake, an imaging biomarker of stress-related neural activity, coronary inflammation (fat attenuation index), and high-risk plaque characteristics were assessed by coronary computed tomography angiography. Their correlation and prognostic values were assessed according to sex. RESULTS: A total of 364 participants (27.7% women and 72.3% men) were enrolled. Among those with heightened stress-related neural activity, women were more likely to have a higher fat attenuation index (43.0% versus 24.0%; P=0.004), while men had a higher frequency of high-risk plaques (53.7% versus 39.3%; P=0.036). High amygdalar 18F-flourodeoxyglucose uptake (B-coefficient [SE], 3.62 [0.21]; P<0.001) was selected as the strongest predictor of fat attenuation index in a fully adjusted linear regression model in women, and the first-order interaction term consisting of sex and stress-related neural activity was significant (P<0.001). Those with enhanced imaging biomarkers of stress-related neural activity showed increased risk of major adverse cardiovascular event both in women (24.5% versus 5.1%; adjusted hazard ratio, 3.62 [95% CI, 1.14-17.14]; P=0.039) and men (17.2% versus 6.9%; adjusted hazard ratio, 2.72 [95% CI, 1.10-6.69]; P=0.030). CONCLUSIONS: Imaging-assessed stress-related neural activity carried prognostic values irrespective of sex; however, a sex-specific mechanism linking psychological stress to coronary plaque phenotypes existed in the current hypothesis-generating study. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT05545618.

A deep learning model based on MRI for prediction of vessels encapsulating tumour clusters and prognosis in hepatocellular carcinoma.

PURPOSE: This study aimed to build and evaluate a deep learning (DL) model to predict vessels encapsulating tumor clusters (VETC) and prognosis preoperatively in patients with hepatocellular carcinoma (HCC). METHODS: 320 pathologically confirmed HCC patients (58 women and 262 men) from two hospitals were included in this retrospective study. Institution 1 (n = 219) and Institution 2 (n = 101) served as the training and external test cohorts, respectively. Tumors were evaluated three-dimensionally and regions of interest were segmented manually in the arterial, portal venous, and delayed phases (AP, PP, and DP). Three ResNet-34 DL models were developed, consisting of three models based on a single sequence. The fusion model was developed by inputting the prediction probability of the output from the three single-sequence models into logistic regression. The area under the receiver operating characteristic curve (AUC) was used to compare performance, and the Delong test was used to compare AUCs. Early recurrence (ER) was defined as recurrence within two years of surgery and early recurrence-free survival (ERFS) rate was evaluated by Kaplan-Meier survival analysis. RESULTS: Among the 320 HCC patients, 227 were VETC- and 93 were VETC+ . In the external test cohort, the fusion model showed an AUC of 0.772, a sensitivity of 0.80, and a specificity of 0.61. The fusion model-based prediction of VETC high-risk and low-risk categories exhibits a significant difference in ERFS rates, akin to the outcomes observed in VETC + and VETC- confirmed through pathological analyses (p < 0.05). CONCLUSIONS: A DL framework based on ResNet-34 has demonstrated potential in facilitating non-invasive prediction of VETC as well as patient prognosis.

Targeted Delivery of Geraniol via Hyaluronic Acid-Conjugation Enhances Its Anti-Tumor Activity Against Prostate Cancer.

Background: Targeted delivery systems have been developed to improve cancer treatment by reducing side effects and enhancing drug efficacy. Geraniol, a natural product, has demonstrated promising anti-cancer effects in various cancer types, including prostate cancer, which is the most commonly diagnosed cancer in men. Hyaluronic acid (HA), a natural carrier targeting CD44-positive prostate cancer cells, can be utilized in a targeted delivery system. Purpose: This study investigated the efficacy of a conjugate of HA and geraniol linked via a disulfide bond linker (HA-SS-Geraniol) in prostate cancer. Materials and Methods: The cytotoxicity of HA-SS-Geraniol was evaluated on human PC-3 prostate cancer cells. Flow cytometry was used to assess its effects on mitochondrial membrane potential, apoptosis, and cell cycle arrest. Additionally, proteomic analysis was conducted to explore the underlying mechanism of action induced by HA-SS-Geraniol treatment. A subcutaneous xenograft tumor model was established in nude mice to evaluate the toxicity and efficacy of HA-SS-Geraniol in vivo. Results: The results demonstrated that HA-SS-Geraniol exhibited potent cytotoxicity against PC-3 prostate cancer cells by inducing mitochondrial membrane potential loss and apoptosis in vitro. The proteomic analysis further supported the hypothesis that HA-SS-Geraniol induces cell death through mitochondria-mediated apoptosis, as evidenced by differential protein expression. The in vivo mouse model confirmed the safety of HA-SS-Geraniol and its ability to inhibit tumor growth. Conclusion: HA-SS-Geraniol holds promise as a biologically safe and potentially effective therapeutic agent for prostate cancer treatment. Its targeted delivery system utilizing HA as a carrier shows potential for improving the efficacy of geraniol in cancer therapy.

Preoperative evaluating early recurrence in resectable pancreatic ductal adenocarcinoma by using CT radiomics.

OBJECTIVE: To investigate the feasibility of a radiomics model based on contrast-enhanced CT for preoperatively predicting early recurrence after curative resection in patients with resectable pancreatic ductal adenocarcinoma (PDAC). METHODS: One hundred and eighty-six patients with resectable PDAC who underwent curative resection were included and allocated to training set (131 patients) and validation set (55 patients). Radiomics features were extracted from arterial phase and portal venous phase images. The Mann-Whitney U test and least absolute shrinkage and selection operator (LASSO) regression were used for feature selection and radiomics signature construction. The radiomics model based on radiomics signature and clinical features was developed by the multivariate logistic regression analysis. Performance of the radiomics model was investigated by the area under the receiver operating characteristic (ROC) curve. RESULTS: The radiomics signature, consisting of three arterial phase and three venous phase features, showed optimal prediction performance for early recurrence in both training (AUC = 0.73) and validation sets (AUC = 0.66). Multivariate logistic analysis identified the radiomics signature (OR, 2.58; 95% CI 2.36-3.17; p = 0.002) and clinical stage (OR, 1.60; 95% CI 1.15-2.30; p = 0.007) as independent predictors. The AUC values for risk evaluation of early recurrence using the radiomics model incorporating clinical stage were 0.80 (training set) and 0.75 (validation set). CONCLUSION: The radiomics-based model integrating with clinical stage can predict early recurrence after upfront surgery in patients with resectable PDAC.

Predictive value of triple negative breast cancer based on DCE-MRI multi-phase full-volume ROI clinical radiomics model.

BACKGROUND: Since no studies compared the value of radiomics features of distinct phases of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) for predicting triple-negative breast cancer (TNBC). PURPOSE: To identify the optimal phase of DCE-MRI for diagnosing TNBC and, in combination with clinical factors, to develop a clinical-radiomics model to well predict TNBC. MATERIAL AND METHODS: This retrospective study included 158 patients with pathology-confirmed breast cancer, including 38 cases of TNBC. The patients were randomly divided into the training and validation set (7:3). Eight radiomics models were built based on eight DCE-MR phases, and their performances were evaluated using receiver operating characteristic curve (ROC) and DeLong's test. The Radscore derived from the best radiomics model was integrated with independent clinical risk factors to construct a clinical-radiomics predictive model, and evaluate its performance using ROC analysis, calibration, and decision curve analyses. RESULTS: WHO classification, margin, and T2-weighted (T2W) imaging signals were significantly correlated with TNBC and independent risk factors for TNBC (P<0.05). The clinical model yielded areas under the curve (AUCs) of 0.867 and 0.843 in the training and validation sets, respectively. The radiomics model based on DCEphase7 achieved the highest efficacy, with an AUC of 0.818 and 0.777. The AUC of the clinical-radiomics model was 0.936 and 0.886 in the training and validation sets, respectively. The decision curve showed the clinical utility of the clinical-radiomics model. CONCLUSION: The radiomics features of DCE-MRI had the potential to predict TNBC and could improve the performance of clinical risk factors for preoperative personalized prediction of TNBC.

Effects of MRI radiomics combined with clinical data in evaluating lymph node metastasis in mrT1-3a staging rectal cancer.

Objective: To investigate the value of a clinical-MRI radiomics model based on clinical characteristics and T2-weighted imaging (T2WI) for preoperatively evaluating lymph node (LN) metastasis in patients with MRI-predicted low tumor (T) staging rectal cancer (mrT1, mrT2, and mrT3a with extramural spread ≤ 5 mm). Methods: This retrospective study enrolled 303 patients with low T-staging rectal cancer (training cohort, n = 213, testing cohort n = 90). A total of 960 radiomics features were extracted from T2WI. Minimum redundancy and maximum relevance (mRMR) and support vector machine were performed to select the best performed radiomics features for predicting LN metastasis. Multivariate logistic regression analysis was then used to construct the clinical and clinical-radiomics combined models. The model performance for predicting LN metastasis was assessed by receiver operator characteristic curve (ROC) and clinical utility implementing a nomogram and decision curve analysis (DCA). The predictive performance for LN metastasis was also compared between the combined model and human readers (2 seniors). Results: Fourteen radiomics features and 2 clinical characteristics were selected for predicting LN metastasis. In the testing cohort, a higher positive predictive value of 75.9% for the combined model was achieved than those of the clinical model (44.8%) and two readers (reader 1: 54.9%, reader 2: 56.3%) in identifying LN metastasis. The interobserver agreement between 2 readers was moderate with a kappa value of 0.416. A clinical-radiomics nomogram and decision curve analysis demonstrated that the combined model was clinically useful. Conclusion: T2WI-based radiomics combined with clinical data could improve the efficacy in noninvasively evaluating LN metastasis for the low T-staging rectal cancer and aid in tailoring treatment strategies.

A radiomics nomogram for predicting postoperative recurrence in esophageal squamous cell carcinoma.

Purpose: To establish and validate a radiomics nomogram for predicting recurrence of esophageal squamous cell carcinoma (ESCC) after esophagectomy with curative intent. Materials and methods: The medical records of 155 patients who underwent surgical treatment for pathologically confirmed ESCC were collected. Patients were randomly divided into a training group (n=109) and a validation group (n=46) in a 7:3 ratio. ​Tumor regions are accurately segmented in computed tomography images of enrolled patients. Radiomic features were then extracted from the segmented tumors. We selected the features by Max-relevance and min-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) methods. A radiomics signature was then built by logistic regression analysis. To improve predictive performance, a radiomics nomogram that incorporated the radiomics signature and independent clinical predictors was built. Model performance was evaluated by receiver operating characteristic (ROC) curve, calibration curve, and decision curve analyses (DCA). Results: We selected the five most relevant radiomics features to construct the radiomics signature. The radiomics model had general discrimination ability with an area under the ROC curve (AUC) of 0.79 in the training set that was verified by an AUC of 0.76 in the validation set. The radiomics nomogram consisted of the radiomics signature, and N stage showed excellent predictive performance in the training and validation sets with AUCs of 0.85 and 0.83, respectively. Furthermore, calibration curves and the DCA analysis demonstrated good fit and clinical utility of the radiomics nomogram. Conclusion: We successfully established and validated a prediction model that combined radiomics features and N stage, which can be used to predict four-year recurrence risk in patients with ESCC who undergo surgery.

Doxorubicin-Loaded Liposome with the Function of "Killing Two Birds with One Stone" against Glioma.

The blood-brain barrier (BBB) continues to be one of the main clinical obstacles in the treatment of glioma. Current chemotherapies always bring many different side effects, some even permanent. To date, nanomaterial-based vehicles have shown great potential in treating glioma. Herein, we developed a dual targeting liposomal delivery vector loaded with the anticancer drug doxorubicin (DOX) to treat glioma. SS31, a small peptide, has shown dual targeting effects of penetrating the BBB and specifically targeting mitochondria. In this study, a new liposomal delivery system, LS-DOX, was prepared by modifying DOX-loaded liposomes with SS31 for the treatment of in situ glioma. The liposomes demonstrated a high drug encapsulation rate and drug-loading capacity, satisfactory biocompatibility, high glioma accumulation ability, and good stability in vitro. Experimental results showed that the liposomes could effectively cross the BBB and target gliomas, and mitochondria-targeting of SS31 enhances cell uptake. In addition, the liposomes showed a good therapeutic effect on nude mice with glioma in situ with no obvious toxicity and side effects. Therefore, the present research will provide a novel alternative and reference for the effective treatment of glioma.

Development and Validation of a Radiomics Nomogram for Liver Metastases Originating from Gastric and Colorectal Cancer.

The origin of metastatic liver tumours (arising from gastric or colorectal sources) is closely linked to treatment choices and survival prospects. However, in some instances, the primary lesion remains elusive even after an exhaustive diagnostic investigation. Consequently, we have devised and validated a radiomics nomogram for ascertaining the primary origin of liver metastases stemming from gastric cancer (GCLMs) and colorectal cancer (CCLMs). This retrospective study encompassed patients diagnosed with either GCLMs or CCLMs, comprising a total of 277 GCLM cases and 278 CCLM cases. Radiomic characteristics were derived from venous phase computed tomography (CT) scans, and a radiomics signature (RS) was computed. Multivariable regression analysis demonstrated that gender (OR = 3.457; 95% CI: 2.102-5.684; p < 0.001), haemoglobin levels (OR = 0.976; 95% CI: 0.967-0.986; p < 0.001), carcinoembryonic antigen (CEA) levels (OR = 0.500; 95% CI: 0.307-0.814; p = 0.005), and RS (OR = 2.147; 95% CI: 1.127-4.091; p = 0.020) exhibited independent associations with GCLMs as compared to CCLMs. The nomogram, combining RS with clinical variables, demonstrated strong discriminatory power in both the training (AUC = 0.71) and validation (AUC = 0.78) cohorts. The calibration curve, decision curve analysis, and clinical impact curves revealed the clinical utility of this nomogram and substantiated its enhanced diagnostic performance.

CT-based radiomics nomogram analysis for assessing BRCA mutation status in patients with high-grade serous ovarian cancer.

BACKGROUND: Radiomics nomogram analysis is widely preoperatively used to assess gene mutations in various tumors. PURPOSE: To explore the value of computed tomography (CT)-based radiomics nomogram analysis for assessing BRCA gene mutation status of patients with high-grade serous ovarian cancer (HGSOC). MATERIAL AND METHODS: In total, 96 patients with HGSOC were retrospectively screened and randomly divided into primary (n = 68) and validation cohorts (n = 28). The clinical model was constructed based on clinical features and CT morphological features using univariate and multivariate logistic analyses. Maximum-relevance and minimum-redundancy (mRMR) and least absolute shrinkage and selection operator (LASSO) were performed for feature dimensionality reduction and radiomics score was calculated. The nomogram model combining the clinical model and the radiomics score was constructed using multivariate logistic regression. Receiver operating characteristic (ROC) curves were generated to assess models' performance. The calibration analysis and decision curve analysis (DCA) were also performed. RESULTS: The clinical model consisted of CA125 level and supradiaphragmatic lymphadenopathy and yielded an area under the curve (AUC) of 0.69 (primary cohort) and 0.81 (validation cohort). The radiomics model was built with seven selected features and showed an AUC of 0.87 (primary cohort) and 0.81 (validation cohort). The nomogram finally showed the highest AUC of 0.89 (primary cohort) and 0.87 (validation cohort). The nomogram presented favorable calibrations in both the primary and validation cohorts. DCA further confirmed the clinical benefits of the constructed nomogram. CONCLUSION: CT-based radiomics nomogram provides a non-invasive method to discriminate BRCA gene mutation status of HGSOC and potentially helps develop precise medical strategies.

A Triple-Targeted Rutin-Based Self-Assembled Delivery Vector for Treating Ischemic Stroke by Vascular Normalization and Anti-Inflammation via ACE2/Ang1-7 Signaling.

Changes in the cerebral microenvironment caused by acute ischemic stroke-reperfusion are the main obstacle to the recovery of neurological function and an important cause of stroke recurrence after thrombolytic therapy. The intracerebral microenvironment after ischemia-reperfusion reduces the neuroplasticity of the penumbra and ultimately leads to permanent neurological damage. To overcome this challenge, we developed a triple-targeted self-assembled nanodelivery system, which combines the neuroprotective drug rutin with hyaluronic acid through esterification to form a conjugate, and then connected SS-31, a small peptide that can penetrate the blood brain barrier and target mitochondria. Brain targeting, CD44-mediated endocytosis, hyaluronidase 1-mediated degradation, and the acidic environment synergistically promoted the enrichment of nanoparticles and drug release in the injured area. Results demonstrate that rutin has a high affinity for ACE2 receptors on the cell membrane and can directly activate ACE2/Ang1-7 signaling, maintain neuroinflammation, and promote penumbra angiogenesis and normal neovascularization. Importantly, this delivery system enhanced the overall plasticity of the injured area and significantly reduced neurological damage after stroke. The relevant mechanism was expounded from the aspects of behavior, histology, and molecular cytology. All results suggest that our delivery system may be an effective and safe strategy for the treatment of acute ischemic stroke-reperfusion injury.

Assessing synchronous ovarian metastasis in gastric cancer patients using a clinical-radiomics nomogram based on baseline abdominal contrast-enhanced CT: a two-center study.

BACKGROUND: To build and validate a radiomics nomogram based on preoperative CT scans and clinical data for detecting synchronous ovarian metastasis (SOM) in female gastric cancer (GC) cases. METHODS: Pathologically confirmed GC cases in 2 cohorts were retrospectively enrolled. All cases had presurgical abdominal contrast-enhanced CT and pelvis contrast-enhanced MRI and pathological examinations for any suspicious ovarian lesions detected by MRI. Cohort 1 cases (n = 101) were included as the training set. Radiomics features were obtained to develop a radscore. A nomogram combining the radscore and clinical factors was built to detect SOM. The bootstrap method was carried out in cohort 1 as internal validation. External validation was carried out in cohort 2 (n = 46). Receiver operating characteristic (ROC) curve analysis, decision curve analysis (DCA) and the confusion matrix were utilized to assess the performances of the radscore, nomogram and subjective evaluation model. RESULTS: The nomogram, which combined age and the radscore, displayed a higher AUC than the radscore and subjective evaluation (0.910 vs 0.827 vs 0.773) in the training cohort. In the external validation cohort, the nomogram also had a higher AUC than the radscore and subjective evaluation (0.850 vs 0.790 vs 0.675). DCA and the confusion matrix confirmed the nomogram was superior to the radscore in both cohorts. CONCLUSIONS: This pilot study showed that a nomogram model combining the radscore and clinical characteristics is useful in detecting SOM in female GC cases. It may be applied to improve clinical treatment and is superior to subjective evaluation or the radscore alone.