Generation of virtual monoenergetic images at 40 keV of the upper abdomen and image quality evaluation based on generative adversarial networks.

BACKGROUND: Abdominal CT scans are vital for diagnosing abdominal diseases but have limitations in tissue analysis and soft tissue detection. Dual-energy CT (DECT) can improve these issues by offering low keV virtual monoenergetic images (VMI), enhancing lesion detection and tissue characterization. However, its cost limits widespread use. PURPOSE: To develop a model that converts conventional images (CI) into generative virtual monoenergetic images at 40 keV (Gen-VMI40keV) of the upper abdomen CT scan. METHODS: Totally 444 patients who underwent upper abdominal spectral contrast-enhanced CT were enrolled and assigned to the training and validation datasets (7:3). Then, 40-keV portal-vein virtual monoenergetic (VMI40keV) and CI, generated from spectral CT scans, served as target and source images. These images were employed to build and train a CI-VMI40keV model. Indexes such as Mean Absolute Error (MAE), Peak Signal-to-Noise Ratio (PSNR), and Structural Similarity (SSIM) were utilized to determine the best generator mode. An additional 198 cases were divided into three test groups, including Group 1 (58 cases with visible abnormalities), Group 2 (40 cases with hepatocellular carcinoma [HCC]) and Group 3 (100 cases from a publicly available HCC dataset). Both subjective and objective evaluations were performed. Comparisons, correlation analyses and Bland-Altman plot analyses were performed. RESULTS: The 192nd iteration produced the best generator mode (lower MAE and highest PSNR and SSIM). In the Test groups (1 and 2), both VMI40keV and Gen-VMI40keV significantly improved CT values, as well as SNR and CNR, for all organs compared to CI. Significant positive correlations for objective indexes were found between Gen-VMI40keV and VMI40keV in various organs and lesions. Bland-Altman analysis showed that the differences between both imaging types mostly fell within the 95% confidence interval. Pearson's and Spearman's correlation coefficients for objective scores between Gen-VMI40keV and VMI40keV in Groups 1 and 2 ranged from 0.645 to 0.980. In Group 3, Gen-VMI40keV yielded significantly higher CT values for HCC (220.5HU vs. 109.1HU) and liver (220.0HU vs. 112.8HU) compared to CI (p < 0.01). The CNR for HCC/liver was also significantly higher in Gen-VMI40keV (2.0 vs. 1.2) than in CI (p < 0.01). Additionally, Gen-VMI40keV was subjectively evaluated to have a higher image quality compared to CI. CONCLUSION: CI-VMI40keV model can generate Gen-VMI40keV from conventional CT scan, closely resembling VMI40keV.

POLR2J expression promotes glioblastoma malignancy by regulating oxidative stress and the STAT3 signaling pathway.

Glioblastoma is the most common cancer in the brain, resistant to conventional therapy and prone to recurrence. Therefore, it is crucial to explore novel therapeutics strategies for the treatment and prognosis of GBM. In this study, through analyzing online datasets, we elucidated the expression and prognostic value of POLR2J and its co-expressed genes in GBM patients. Functional experiments, including assays for cell apoptosis and cell migration, were used to explore the effects of POLR2J and vorinostat on the proliferation and migration of GBM cells. The highest overexpression of POLR2J, among all cancer types, was observed in GBM. Furthermore, high expression of POLR2J or its co-expressed genes predicted a poor outcome in GBM patients. DNA replication pathways were significantly enriched in the GBM clinical samples with high POLR2J expression, and POLR2J suppression inhibited proliferation and triggered cell cycle G1/S phase arrest in GBM cells. Moreover, POLR2J silencing activated the unfolded protein response (UPR) and significantly enhanced the anti-GBM activity of vorinostat by suppressing cell proliferation and inducing apoptosis. Additionally, POLR2J could interact with STAT3 to promote the metastatic potential of GBM cells. Our study identifies POLR2J as a novel oncogene in GBM progression and provides a promising strategy for the chemotherapeutic treatment of GBM.

The role of perirenal adipose tissue deposition in chronic kidney disease progression: Mechanisms and therapeutic implications.

Chronic kidney disease (CKD) represents a significant and escalating global health challenge, with morbidity and mortality rates rising steadily. Evidence increasingly implicates perirenal adipose tissue (PRAT) deposition as a contributing factor in the pathogenesis of CKD. This review explores how PRAT deposition may exert deleterious effects on renal structure and function. The anatomical proximity of PRAT to the kidneys not only potentially causes mechanical compression but also leads to the dysregulated secretion of adipokines and inflammatory mediators, such as adiponectin, leptin, visfatin, tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6), and exosomes. Additionally, PRAT deposition may contribute to renal lipotoxicity through elevated levels of free fatty acids (FFA), triglycerides (TAG), diacylglycerol (DAG), and ceramides (Cer). PRAT deposition is also linked to the hyperactivation of the renin-angiotensin-aldosterone system (RAAS), which further exacerbates CKD progression. Recognizing PRAT deposition as an independent risk factor for CKD underscores the potential of targeting PRAT as a novel strategy for the prevention and management of CKD. This review further discusses interventions that could include measuring PRAT thickness to establish a baseline, managing metabolic risk factors that promote its deposition, and inhibiting key PRAT-induced signaling pathways.

Discovery and characterization of novel FGFR1 inhibitors in triple-negative breast cancer via hybrid virtual screening and molecular dynamics simulations.

The overexpression of FGFR1 is thought to significantly contribute to the progression of triple-negative breast cancer (TNBC), impacting aspects such as tumorigenesis, growth, metastasis, and drug resistance. Consequently, the pursuit of effective inhibitors for FGFR1 is a key area of research interest. In response to this need, our study developed a hybrid virtual screening method. Utilizing KarmaDock, an innovative algorithm that blends deep learning with molecular docking, alongside Schrödinger's Residue Scanning. This strategy led us to identify compound 6, which demonstrated promising FGFR1 inhibitory activity, evidenced by an IC50 value of approximately 0.24 nM in the HTRF bioassay. Further evaluation revealed that this compound also inhibits the FGFR1 V561M variant with an IC50 value around 1.24 nM. Our subsequent investigations demonstrate that Compound 6 robustly suppresses the migration and invasion capacities of TNBC cell lines, through the downregulation of p-FGFR1 and modulation of EMT markers, highlighting its promise as a potent anti-metastatic therapeutic agent. Additionally, our use of molecular dynamics simulations provided a deeper understanding of the compound's specific binding interactions with FGFR1.

Developing a prognostic model for skin melanoma based on the persistent tumor mutation burden and determining IL17REL as a therapeutic target.

BACKGROUND: One popular and well-established marker for the immune checkpoint blockade (ICB) response is tumor mutation burden (TMB). Persistent TMB (pTMB), a subset of TMB, provides a better indicator to predict patient ICB therapy outcomes, as shown by some studies. Immune checkpoint drugs have significantly changed how melanoma is treated in recent years. METHODS: In this study, we integrated the TCGA-SKCM database and data of pTMB of TCGA from the paper that first mentioned pTMB and analyzed mutational and Immune characteristics associated with pTMB level in SKCM. Next, the predictive DEGs were identified the subgroups of pTMB by Cox regression and LASSO analyses to construct a pTMB-related signature. Finally, the expression and Biological functions of signature genes was detected, and further validated in vitro assay. RESULTS: In the current research, we explored the mutational and immunological features related to the level of TMB in cutaneous melanoma (CM). The high-pTMB subgroup exhibited an increasing incidence of gene changes and higher levels of immune cell infiltration. Subsequently, we established a pTMB-related signature based on the predictive DEGs and found the biological features and immune-associated variables between two distinct risk groups. Lastly, the results of the clinical sample validation demonstrated that the expression of IL17REL was down-regulated in the collected samples of individuals with CM. The in vitro assay results indicated that IL17REL effectively suppressed the proliferation, clonality, and migration of CM cells. CONCLUSION: In conclusion, we have developed a prediction model associated with TMB and subsequently validated the potential influence of IL17REL on Overall Survival (OS) in patients diagnosed with melanoma.

Cerebrospinal fluid CXCL13 concentration for diagnosis of neurosyphilis: a systematic review and meta-analysis.

OBJECTIVE: To systematically assess the diagnostic accuracy of CXCL13 testing of cerebrospinal fluid (CSF) for neurosyphilis diagnosing. DESIGN: Systematic review and meta-analysis. DATA SOURCES: PubMed, Embase, Cochrane Library and Web of Science databases from their inception until 1 May 2023. ELIGIBILITY CRITERIA: Both cross-sectional and case-control diagnostic test studies evaluating the diagnostic value of CSF CXCL13 in diagnosing neurosyphilis were included, with no language restrictions. DATA EXTRACTION AND SYNTHESIS: Two researchers extracted data independently from all finally included articles. The updated Quality Assessment of Diagnostic Accuracy Studies tool was used to assess the quality of the included studies. Quantitative synthesis was done using a bivariate random-effects model. RESULTS: This meta-analysis included seven eligible studies involving a total of 1152 patients with syphilis and 430 patients with neurosyphilis. The pooled sensitivity, specificity and summary area under the curve (AUC) of CSF CXCL13 testing for the diagnosis of neurosyphilis were 0.76 (95% CI 0.64 to 0.85; I2=82%), 0.83 (95% CI 0.80 to 0.85; I2=32.29%) and 0.84 (95% CI 0.81 to 0.87), respectively. Sensitivity analysis confirmed the stability of the combined results. Meta-regression analysis revealed that the heterogeneity of pooled sensitivity was related to different study regions; subgroup analysis indicated that the diagnostic value of CSF CXCL13 testing reported in studies from China was superior to that reported in non-Chinese studies (pooled sensitivity, specificity and summary AUC values were 0.84 (I2=0) vs 0.64 (I2=79.53%), 0.83 (I2=42.03%) vs 0.83 (I2=32.87%) and 0.87 vs 0.83, respectively). The diagnostic value reported in studies with a sample size ≥200, unclassified neurosyphilis and HIV-negative subgroups was superior to the total combined value. CONCLUSIONS: This meta-analysis has demonstrated a reasonable level of accuracy for diagnosis of neurosyphilis with CSF CXCL13 testing. Further multicentre, prospective diagnostic studies, especially in asymptomatic neurosyphilis and HIV-infected patients, are needed to provide more evidence for evaluation before clinical application. PROSPERO REGISTRATION NUMBER: CRD42023414212.

Discovery of potent CSK inhibitors through integrated virtual screening and molecular dynamic simulation.

Oncogenic overexpression or activation of C-terminal Src kinase (CSK) has been shown to play an important role in triple-negative breast cancer (TNBC) progression, including tumor initiation, growth, metastasis, drug resistance. This revelation has pivoted the focus toward CSK as a potential target for novel treatments. However, until now, there are few inhibitors designed to target the CSK protein. Responding to this, our research has implemented a comprehensive virtual screening protocol. By integrating energy-based screening methods with AI-driven scoring functions, such as Attentive FP, and employing rigorous rescoring methods like Glide docking and molecular mechanics generalized Born surface area (MM/GBSA), we have systematically sought out inhibitors of CSK. This approach led to the discovery of a compound with a potent CSK inhibitory activity, reflected by an IC50 value of 1.6 nM under a homogeneous time-resolved fluorescence (HTRF) bioassay. Subsequently, molecule 2 exhibits strong growth inhibition of MD anderson - metastatic breast (MDA-MB) -231, Hs578T, and SUM159 cells, showing a level of growth inhibition comparable to that observed with dasatinib. Treatment with molecule 2 also induced significant G1 phase accumulation and cell apoptosis. Furthermore, we have explored the explicit binding interactions of the compound with CSK using molecular dynamics simulations, providing valuable insights into its mechanism of action.

Integrative analysis of histone acetylation regulated CYP4F12 in esophageal cancer development.

Current therapeutic strategies for esophageal cancer (EC) patients have yielded limited improvements in survival rates. Recent research has highlighted the influence of drug metabolism enzymes (DME) on both drug response and EC development. Our study aims to identify specific DMEs regulated by histone acetylation and to elucidate its molecular and clinical features. CYP4F12 exhibited a notable upregulation subsequent to TSA treatment as evidenced by RNA-seq analysis conducted on the KYSE-150 cell line. The change in gene expression was associated with increased acetylation level of histone 3 K18 and K27 in the promoter. The regulation was dependent on p300. In silicon analysis of both TCGA-ESCA and GSE53624 dataset suggested a critical role of CYP4F12 in EC development as CYP4F12 was downregulated in tumor tissues and predicted better disease-free survival. Gene ontology analysis has uncovered a robust correlation between CYP4F12 and processes related to cell migration, as well as its involvement in cytosine-mediated immune activities. Further investigation into the relationship between immune cells and CYP4F12 expression has indicated an increased level of B cell infiltration in samples with high CYP4F12 expression. CYP4F12 was also negatively correlated with the expression of inhibitory checkpoints. An accurate predictive nomogram model was established combining with clinical factors and CYP4F12 expression. In conclusion, CYP4F12 was crucial in EC development, targeting CYP4F12 may improve the therapeutic efficacy of current treatment in EC patients. Significance Statement CYP4F12 expression was downregulated in EC patients and could be induced by TSA. During EC development, CYP4F12 was linked to reduced cell migration and increased infiltration of B cells. CYP4F12 also is a biomarker as prognostic predictors and therapeutic guide in EC patients.

Gut microbiota-derived cholic acid mediates neonatal brain immaturity and white matter injury under chronic hypoxia.

Chronic hypoxia, common in neonates, disrupts gut microbiota balance, which is crucial for brain development. This study utilized cyanotic congenital heart disease (CCHD) patients and a neonatal hypoxic rat model to explore the association. Both hypoxic rats and CCHD infants exhibited brain immaturity, white matter injury (WMI), brain inflammation, and motor/learning deficits. Through 16s rRNA sequencing and metabolomic analysis, a reduction in B. thetaiotaomicron and P. distasonis was identified, leading to cholic acid accumulation. This accumulation triggered M1 microglial activation and inflammation-induced WMI. Administration of these bacteria rescued cholic acid-induced WMI in hypoxic rats. These findings suggest that gut microbiota-derived cholic acid mediates neonatal WMI and brain inflammation, contributing to brain immaturity under chronic hypoxia. Therapeutic targeting of these bacteria provides a non-invasive intervention for chronic hypoxia patients.

Consolidation chemotherapy after definitive concurrent chemoradiotherapy in patients with inoperable esophageal squamous cell carcinoma: a multicenter non-inferiority phase III randomized clinical trial.

BACKGROUND: Definitive concurrent chemoradiotherapy (dCCRT) is the gold standard for the treatment of locally advanced esophageal squamous cell carcinoma (ESCC). However, the potential benefits of consolidation chemotherapy after dCCRT in patients with esophageal cancer remain debatable. Prospective randomized controlled trials comparing the outcomes of dCCRT with or without consolidation chemotherapy in patients with ESCC are lacking. In this study, we aim to generate evidence regarding consolidation chemotherapy efficacy in patients with locally advanced, inoperable ESCC. METHODS: This is a multicenter, prospective, open-label, phase-III randomized controlled trial comparing non-inferiority of dCCRT alone to consolidation chemotherapy following dCCRT. In total, 600 patients will be enrolled and randomly assigned in a 1:1 ratio to receive either consolidation chemotherapy after dCCRT (Arm A) or dCCRT alone (Arm B). Overall survival will be the primary endpoint, whereas progression-free survival, locoregional progression-free survival, distant metastasis-free survival, and treatment-related toxicity will be the secondary endpoints. DISCUSSION: This study aid in further understanding the effects of consolidation chemotherapy after dCCRT in patients with locally advanced, inoperable ESCC. TRIAL REGISTRATION: ChiCTR1800017646.

Romidepsin exhibits anti-esophageal squamous cell carcinoma activity through the DDIT4-mTORC1 pathway.

Esophageal squamous cell carcinoma (ESCC) is one of the most common human malignancies worldwide and is associated with high morbidity and mortality. Current treatment options are limited, highlighting the need for development of novel effective agents. Here, a high-throughput drug screening (HTS) was performed using ESCC cell lines in both two- and three-dimensional culture systems to screen compounds that have anti-ESCC activity. Our screen identified romidepsin, a histone deactylase inhibitor, as a potential anti-ESCC agent. Romidepsin treatment decreased cell viability, induced apoptosis and cell cycle arrest in ESCC cell lines, and these findings were confirmed in ESCC cell line-derived xenografted (CDX) mouse models. Mechanically, romidepsin induced transcriptional upregulation of DNA damage-inducible transcript 4 (DDIT4) gene by histone hyperacetylation at its promoter region, leading to the inhibition of mammalian target of rapamycin complex 1 (mTORC1) pathway. Furthermore, romidepsin exhibited better efficacy and safety compared to the conventional therapeutic drugs in ESCC patient-derived xenografted (PDX) mouse models. These data indicate that romidepsin may be a novel option for anti-ESCC therapy.

Vitamin D levels in idiopathic inflammatory myopathy patients: a meta-analysis.

PURPOSE: This meta-analysis aimed to explore correlations between vitamin D and idiopathic inflammatory myopathy (IIM). METHODS: A comprehensive database search was conducted on 13 October 2020. Mean differences (MDs) and aggregated risk ratios (RR) with 95% confidence intervals (CIs) were used to determine the correlation between vitamin D deficiency (VDD) and IIM. Statistical analysis was performed with RevMan 5.4 and Stata15, statistical significance was set at p < 0.05. RESULTS: Search revealed five studies with 286 IIM patients and 480 healthy controls. Results with random-effects modeling indicated that serum vitamin D levels were significantly lower in IIM patients than in healthy controls (MD = -13.10 ng/mL; 95% CI: -16.51 to -9.68; p < 0.00001). No differences were found between patients with IIM and other autoimmune diseases on vitamin D levels (MD =-2.65 ng/mL; 95% CI: -11.31-6.01; p = 0.55). In two studies with 185 IIM patients, those with low vitamin D levels exhibited higher creatine kinase levels (MD = 85.20 IU/L; 95% CI: 72.67-97.73; p < 0.00001) than those with normal vitamin D levels. VDD was correlated with an increased risk of IIM (RR = 3.24, 95% CI: 1.81-5.79; p < 0.0001). CONCLUSION: This meta-analysis showed correlations between vitamin D level and IIM. The results indicated, VDD may be a risk factor for IIM, a determinant of immune dysregulation in IIM, or a consequence of IIM. Also, it implied further research to determine whether vitamin D supplementation is beneficial for patients with IIM.

A PET/CT radiomics model for predicting distant metastasis in early-stage non-small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study.

OBJECTIVES: Stereotactic body radiotherapy (SBRT) is a treatment option for patients with early-stage non-small cell lung cancer (NSCLC) who are unfit for surgery. Some patients may experience distant metastasis. This study aimed to develop and validate a radiomics model for predicting distant metastasis in patients with early-stage NSCLC treated with SBRT. METHODS: Patients at five institutions were enrolled in this study. Radiomics features were extracted based on the PET/CT images. After feature selection in the training set (from Tianjin), CT-based and PET-based radiomics signatures were built. Models based on CT and PET signatures were built and validated using external datasets (from Zhejiang, Zhengzhou, Shandong, and Shanghai). An integrated model that included CT and PET radiomic signatures was developed. The performance of the proposed model was evaluated in terms of its discrimination, calibration, and clinical utility. Multivariate logistic regression was used to calculate the probability of distant metastases. The cutoff value was obtained using the receiver operator characteristic curve (ROC), and the patients were divided into high- and low-risk groups. Kaplan-Meier analysis was used to evaluate the distant metastasis-free survival (DMFS) of different risk groups. RESULTS: In total, 228 patients were enrolled. The median follow-up time was 31.4 (2.0-111.4) months. The model based on CT radiomics signatures had an area under the curve (AUC) of 0.819 in the training set (n = 139) and 0.786 in the external dataset (n = 89). The PET radiomics model had an AUC of 0.763 for the training set and 0.804 for the external dataset. The model combining CT and PET radiomics had an AUC of 0.835 for the training set and 0.819 for the external dataset. The combined model showed a moderate calibration and a positive net benefit. When the probability of distant metastasis was greater than 0.19, the patient was considered to be at high risk. The DMFS of patients with high- and low-risk was significantly stratified (P < 0.001). CONCLUSIONS: The proposed PET/CT radiomics model can be used to predict distant metastasis in patients with early-stage NSCLC treated with SBRT and provide a reference for clinical decision-making. In this study, the model was established by combining CT and PET radiomics signatures in a moderate-quantity training cohort of early-stage NSCLC patients treated with SBRT and was successfully validated in independent cohorts. Physicians could use this easy-to-use model to assess the risk of distant metastasis after SBRT. Identifying subgroups of patients with different risk factors for distant metastasis is useful for guiding personalized treatment approaches.

Multi-omics and Multi-VOIs to predict esophageal fistula in esophageal cancer patients treated with radiotherapy.

OBJECTIVE: This study aimed to develop a prediction model for esophageal fistula (EF) in esophageal cancer (EC) patients treated with intensity-modulated radiation therapy (IMRT), by integrating multi-omics features from multiple volumes of interest (VOIs). METHODS: We retrospectively analyzed pretreatment planning computed tomographic (CT) images, three-dimensional dose distributions, and clinical factors of 287 EC patients. Nine groups of features from different combination of omics [Radiomics (R), Dosiomics (D), and RD (the combination of R and D)], and VOIs [esophagus (ESO), gross tumor volume (GTV), and EG (the combination of ESO and GTV)] were extracted and separately selected by unsupervised (analysis of variance (ANOVA) and Pearson correlation test) and supervised (Student T test) approaches. The final model performance was evaluated using five metrics: average area under the receiver-operator-characteristics curve (AUC), accuracy, precision, recall, and F1 score. RESULTS: For multi-omics using RD features, the model performance in EG model shows: AUC, 0.817 ± 0.031; 95% CI 0.805, 0.825; p < 0.001, which is better than single VOI (ESO or GTV). CONCLUSION: Integrating multi-omics features from multi-VOIs enables better prediction of EF in EC patients treated with IMRT. The incorporation of dosiomics features can enhance the model performance of the prediction.

Second haploidentical bone marrow transplantation with antithymocyte antibody-containing conditioning regimen for graft failure in eight patients with severe aplastic anemia.

The effects of a second haploidentical bone marrow transplantation with an antithymocyte antibody-containing conditioning regimen after graft failure in patients with severe aplastic anemia remain unclear. Eight severe aplastic anemia patients with graft failure with a median age of 12.5 (range, 3-22) years were retrospectively reviewed. At the second transplantation, they received a median mononuclear cell number of 15.7 (range, 11.2-20.9) × 108/kg or a median CD34+ cell number of 6.2 (range, 2.5-17.5) × 106/kg. They were all successfully engrafted, with a median time of 12.5 (range, 11-16) days for neutrophils and 24 (range, 14-50) days for platelets. Three patients developed skin acute graft-versus-host disease Grades I-II, and another 3 developed limited chronic graft-versus-host disease. All patients successfully recovered after treatment with methylprednisolone (0.5-1 mg/kg/day) and tacrolimus. One patient each died of respiratory failure caused by multidrug-resistant Klebsiella pneumoniae at 8 months and invasive fungal disease at 23 months after transplantation. Six patients survived with a 5-year estimated overall survival of 75% and a median follow-up time of 61 (range, 8-129) months. A second haploidentical bone marrow transplantation with an antithymocyte antibody-containing conditioning regimen was feasible for saving severe aplastic anemia patients with graft failure.

Discovery of a potent and selective PARP1 degrader promoting cell cycle arrest via intercepting CDC25C-CDK1 axis for treating triple-negative breast cancer.

PARP1 is a multifaceted component of DNA repair and chromatin remodeling, making it an effective therapeutic target for cancer therapy. The recently reported proteolytic targeting chimera (PROTAC) could effectively degrade PARP1 through the ubiquitin-proteasome pathway, expanding the therapeutic application of PARP1 blocking. In this study, a series of nitrogen heterocyclic PROTACs were designed and synthesized through ternary complex simulation analysis based on our previous work. Our efforts have resulted in a potent PARP1 degrader D6 (DC50 = 25.23 nM) with high selectivity due to nitrogen heterocyclic linker generating multiple interactions with the PARP1-CRBN PPI surface, specifically. Moreover, D6 exhibited strong cytotoxicity to triple negative breast cancer cell line MDA-MB-231 (IC50 = 1.04 µM). And the proteomic results showed that the antitumor mechanism of D6 was found that intensifies DNA damage by intercepting the CDC25C-CDK1 axis to halt cell cycle transition in triple-negative breast cancer cells. Furthermore, in vivo study, D6 showed a promising PK property with moderate oral absorption activity. And D6 could effectively inhibit tumor growth (TGI rate = 71.4 % at 40 mg/kg) without other signs of toxicity in MDA-MB-321 tumor-bearing mice. In summary, we have identified an original scaffold and potent PARP1 PROTAC that provided a novel intervention strategy for the treatment of triple-negative breast cancer.

A novel CT-responsive hydrogel for the construction of an organ simulation phantom for the repeatability and stability study of radiomic features.

Radiomic features have demonstrated reliable outcomes in tumor grading and detecting precancerous lesions in medical imaging analysis. However, the repeatability and stability of these features have faced criticism. In this study, we aim to enhance the repeatability and stability of radiomic features by introducing a novel CT-responsive hydrogel material. The newly developed CT-responsive hydrogel, mineralized by in situ metal ions, exhibits exceptional repeatability, stability, and uniformity. Moreover, by adjusting the concentration of metal ions, it achieves remarkable CT similarity comparable to that of human organs on CT scans. To create a phantom, the hydrogel was molded into a universal model, displaying controllable CT values ranging from 53 HU to 58 HU, akin to human liver tissue. Subsequently, 1218 radiomic features were extracted from the CT-responsive hydrogel organ simulation phantom. Impressively, 85-97.2% of the extracted features exhibited good repeatability and stability during coefficient of variability analysis. This finding emphasizes the potential of CT-responsive hydrogel in consistently extracting the same features, providing a novel approach to address the issue of repeatability in radiomic features.

Porphyrin-based Bi-MOFs with Enriched Surface Bi Active Sites for Boosting Photocatalytic CO2 Reduction.

The inherent challenges in using metal-organic frameworks (MOFs) for photocatalytic CO2 reduction are the combination of wide-range light harvesting, efficient charge separation and transfer as well as highly exposed catalytic active sites for CO2 activation and reduction. We present here a promising solution to satisfy these requirements together by modulating the crystal facet and surface atomic structure of a porphyrin-based bismuth-MOF (Bi-PMOF). The series of structural and photo-electronic characterizations together with photocatalytic CO2 reduction experiment collectively establish that the enriched Bi active sites on the (010) surface prefer to promote efficient charge separation and transfer as well as the activation and reduction of CO2 . Specifically, the Bi-PMOFs-120-F with enriched surface Bi active sites exhibits optimal photocatalytic CO2 reduction performance to CO (28.61 µmol h-1 g-1 ) and CH4 (8.81 µmol h-1 g-1 ). This work provides new insights to synthesize highly efficient main group p-block metal Bi-MOF photocatalysts for CO2 reduction through a facet-regulation strategy and sheds light on the surface structure-activity relationships of the MOFs.

Serological Biomarker-Based Machine Learning Models for Predicting the Relapse of Ulcerative Colitis.

Purpose: To explore whether machine learning models using serological markers can predict the relapse of Ulcerative colitis (UC). Patients and Methods: This clinical cohort study included 292 UC patients, and serological markers were obtained when patients were discharged from the hospital. Subsequently, four machine learning models including the random forest (RF) model, the logistic regression model, the decision tree, and the neural network were compared to predict the relapse of UC. A nomogram was constructed, and the performance of these models was evaluated by accuracy, sensitivity, specificity, and the area under the receiver operating characteristic curve (AUC). Results: Based on the patients' characteristics and serological markers, we selected the relevant variables associated with relapse and developed a LR model. The novel model including gender, white blood cell count, percentage of leukomonocyte, percentage of monocyte, absolute value of neutrophilic granulocyte, and erythrocyte sedimentation rate was established for predicting the relapse. In addition, the average AUC of the four machine learning models was 0.828, of which the RF model was the best. The AUC of the test group was 0.889, the accuracy was 76.4%, the sensitivity was 78.5%, and the specificity was 76.4%. There were 45 variables in the RF models, and the relative weight coefficients of these variables were determined. Age has the greatest impact on classification results, followed by hemoglobin concentration, white blood cell count, and platelet distribution width. Conclusion: Machine learning models based on serological markers had high accuracy in predicting the relapse of UC. The model can be used to noninvasively predict patient outcomes and can be an effective tool for determining personalized treatment plans.

DMU-212 against EGFR-mutant non-small cell lung cancer via AMPK/PI3K/Erk signaling pathway.

Although some important advances have been achieved in clinical and diagnosis in the past few years, the management of non-small cell lung cancer (NSCLC) is ultimately dissatisfactory due to the low overall cure and survival rates. Epidermal growth factor (EGFR) has been recognized as a carcinogenic driver and is a crucial pharmacological target for NSCLC. DMU-212, an analog of resveratrol, has been reported to have significant inhibitory effects on several types of cancer. However, the effect of DMU-212 on lung cancer remains unclear. Therefore, this study aims to determine the effects and underlying mechanism of DMU-212 on EGFR-mutant NSCLC cells. The data found that the cytotoxicity of DMU-212 on three EGFR-mutant NSCLC cell lines was significantly higher than that of normal lung epithelial cell. Further study showed that DMU-212 can regulate the expression of cell cycle-related proteins including p21 and cyclin B1 to induce G2/M phase arrest in both H1975 and PC9 cells. Moreover, treatment with DMU-212 significantly promoted the activation of AMPK and simultaneously down-regulated the expression of EGFR and the phosphorylation of PI3K, Akt and ERK. In conclusion, our study suggested that DMU-212 inhibited the growth of NSCLCs via targeting of AMPK and EGFR.