TBC1D1 represses glioma progression by altering the integrity of the cytoskeleton.

BACKGROUND: Glioma is one of the most aggressive malignant brain tumors and is characterized by invasive growth and poor prognosis. TBC1D1, a member of the TBC family, is associated with the development of various malignancies. However, the role of TBC1D1 in glioma-genesis remains unclear. METHODS: The effect of TBC1D1 on the prognosis of glioma patients and related influencing factors were analyzed in the Chinese Glioma Genome Atlas (CGGA) and The Cancer Genome Atlas (TCGA) databases. Expression of TBC1D1 in glioma cell lines was detected by western blotting. Cell viability and proliferation were measured by EdU and Colony formation assays, respectively. Transwell and wound healing assays were performed to determine the cell migration and invasion capacities. Immunofluorescence was used to observe actin morphology in the cytoskeleton. RESULTS: We discovered that high TBC1D1 expression in gliomas led to poor prognosis. Downregulation of TBC1D1 in glioma cells significantly inhibited multiple important functions, such as proliferation, migration, and invasion. We further demonstrated that the tumor-inhibitory effect of TBC1D1 might occur through the P-LIMK/cofilin pathway, destroying the cytoskeletal structure and affecting the depolymerization of F-actin, thereby inhibiting glioma migration. CONCLUSION: TBC1D1 affects the balance and integrity of the actin cytoskeleton via cofilin, thereby altering the morphology and aggressiveness of glioma cells. This study provides a new perspective on its role in tumorigenesis, thereby identifying a potential therapeutic target for the treatment of gliomas.

CAFs Homologous Biomimetic Liposome Bearing BET Inhibitor and Pirfenidone Synergistically Promoting Antitumor Efficacy in Pancreatic Ductal Adenocarcinoma.

BRD4 is a member of the BET protein family involved in chromatin remodeling and transcriptional regulation. Several BET inhibitors (BETi) have entered clinical trials, demonstrating potential in inducing cancer cell apoptosis and tumor regression. However, resistance to BETi is common in solid tumors. In pancreatic cancer, it is found that cancer-associated fibroblasts (CAFs) in the tumor microenvironment reduce the BET inhibitor JQ1 sensitivity by inducing BRD4 expression. Moreover, CAFs play a crucial role in the formation of a dense stromal barrier. Therefore, targeting CAFs in the tumor microenvironment of pancreatic cancer not only enhances cancer cells sensitivity to JQ1 but also increases drug perfusion and improves oxygen supply, thus reducing glycolysis and limiting energy supply. To address this challenge, a homologous targeting mechanism utilizing activated fibroblast membrane-coated liposomes is proposed for specific drug precise target to CAFs-rich pancreatic cancer. Additionally, TAT peptides enable liposomes penetration, delivering PFD for targeted anti-fibrotic therapy, reducing extracellular matrix generation and glycolysis, and enhancing JQ1 delivery and sensitivity. In conclusion, the findings indicate the tremendous potential of this CAFs-targeting liposomal delivery system in pancreatic cancer.

Cold atmospheric plasma-enabled platelet vesicle incorporated iron oxide nano-propellers for thrombolysis.

A new approach to treating vascular blockages has been developed to overcome the limitations of current thrombolytic therapies. This approach involves biosafety and multimodal plasma-derived theranostic platelet vesicle incorporating iron oxide constructed nano-propellers platformed technology that possesses fluorescent and magnetic features and manifold thrombus targeting modes. The platform is capable of being guided and visualized remotely to specifically target thrombi, and it can be activated using near-infrared phototherapy along with an actuated magnet for magnetotherapy. In a murine model of thrombus lesion, this proposed multimodal approach showed an approximately 80 % reduction in thrombus residues. Moreover, the new strategy not only improves thrombolysis but also boosts the rate of lysis, making it a promising candidate for time-sensitive thrombolytic therapy.

PFKP confers chemoresistance by upregulating ABCC2 transporter in non-small cell lung cancer.

Background: Chemoresistance is a significant factor contributing to tumor recurrence and treatment failure in non-small cell lung cancer (NSCLC). The phosphofructokinase, platelet (PFKP) is highly expressed in NSCLC and is associated with a poor prognosis. Exploring the molecular mechanism and identifying effective strategies to overcome chemoresistance will have important clinical significance in improving the diagnosis and treatment of NSCLC. Methods: The correlation between PFKP and cisplatin resistance in NSCLC patients was assessed by organoids and immunohistochemistry. The impact of PFKP on the prognosis of NSCLC patients was analyzed using The Cancer Genome Atlas (TCGA) database. In NSCLC cell lines, the expression of PFKP was modulated using lentivirus, and cisplatin sensitivity was assessed by flow cytometry. Subsequently, the therapeutic effect of cisplatin was tested in BALB/c nude mice implanted subcutaneously with tumor cells. We performed luciferase assay and immunohistochemistry (IHC) to investigate the correlation between PFKP and ABCC2 (ATP-binding cassette sub-family C member 2). Results: Overexpression of PFKP was correlated with poorer survival rates in NSCLC patients who received platinum-based chemotherapy. Using NSCLC organoid, we found that the expression of PFKP was elevated in cisplatin (CDDP)-resistant patients with NSCLC. Overexpression of PFKP decreased the sensitivity of NSCLC cells to CDDP, while genetic inhibition of PFKP enhanced CDDP sensitivity both in vitro and in vivo. Furthermore, we found that PFKP upregulated ABCC2 by increasing the levels of phosphorylation of IκBα and nuclear p65 NF-κB subunit protein. Conclusions: PFKP can regulate the expression of ABCC2 through the activation of NF-κB, which in turn promotes chemoresistance in NSCLC. PFKP has the potential to be a personalized therapeutic target for NSCLC patients with chemoresistance.

Lithium chloride induces apoptosis by activating endoplasmic reticulum stress in pancreatic cancer.

Lithium compounds, a classic class of metal complex medicine that target GSK 3ß and are widely known as mood-stabilizer, have recently been reported as potential anti-tumor drugs. The objective of this investigation was to explore the anticancer potential of lithium chloride (LiCl) and elucidate its mode of action in pancreatic cancer cells. The MTT, colony formation, and Edu assay were used to evaluate the impact of LiCl on pancreatic cancer cell proliferation. Various methods were employed to investigate the anti-tumor activity of LiCl and its underlying mechanisms. Cell cycle analysis and apoptosis detection assays were utilized for in vitro experiments, while the orthotopic pancreatic cancer mouse model was employed to evaluate the effectiveness of LiCl treatment in vivo. Furthermore, the impact of LiCl on the proliferation of patient-derived organoids was also studied. The results demonstrated that LiCl inhibited the proliferation of pancreatic cancer (PC) cells, induced G2/M phase arrest, and activated apoptosis. Notably, the triggering of endoplasmic reticulum (ER) stress by LiCl was observed, leading to the activation of the PERK/CHOP/GADD34 pathway, which subsequently promoted apoptosis in PC cells. In the future, Lithium compounds could become an essential adjunct in the treatment of human pancreatic cancer.

A Novel 1000 MPa Grade Ultrafine-Grained Dual-Phase Press Hardening Steel with Superior Oxidation Resistance and High Ductility.

1000 MPa grade low-carbon martensite press hardening steels (PHS) are widely used in energy-absorbing domains of automotive parts, such as the bottom of a B-pillar. To prevent oxide scale formation during hot forming, this PHS is often required to be protected by an additional Al-Si coating. In addition, although the low carbon martensitic microstructure grants it excellent bending toughness, the ductility tends to be limited. In this study, a novel 1000 MPa grade ultrafine-grained (UFG) martensite-ferrite (F-M) dual-phase (DP) PHS with superior oxidation resistance was designed using tailored additions of Cr, Mn, and Si, and refining the initial microstructure. Only 0.55 ± 0.18 µm thick oxide film is formed in the designed steel during austenitizing heating and stamping, which is significantly lower than the 24.6 ± 3.1 µm thick oxide film formed in conventional 1000 MPa grade low-carbon martensite PHS under the identical condition. The superior oxidation resistance of designed steel can be attributed to the rapid formation of the protective Si-rich, Cr-rich, and Mn-rich oxide layers during annealing. Moreover, due to the presence of ferrite and ultrafine microstructure, the designed steel also shows a significant improvement in ductility from 8.5% to 16.8% without sacrificing strength and bending toughness compared with conventional 1000 MPa grade low-carbon martensite PHS.

SLC1A5 is a novel biomarker associated with ferroptosis and the tumor microenvironment: a pancancer analysis.

Solute carrier family 1 member 5 (SLC1A5) is a member of the solute carrier (SLC) superfamily of transporters and plays an important role in tumors as a key transporter of glutamine into cells. However, the relationship between SLC1A5, which is involved in immune regulation, and immune cell infiltration in the tumor microenvironment has not been elucidated, and the relationship between SLC1A5 and ferroptosis is rarely reported. Therefore, we comprehensively analyzed the expression level of SLC1A5 across cancers and compared it with that in normal tissues. Then, the relationship between SLC1A5 expression and the tumor immune microenvironment was analyzed by single-cell analysis, gene set enrichment analysis (GSEA), and Tumor Immune Estimation Resource (TIMER). Next, the correlations of the SLC1A5 expression level with immunotherapy response, immunomodulator expression, tumor mutation burden (TMB) and microsatellite instability (MSI) were evaluated. Finally, in vitro experiments verified that SLC1A5 participates in ferroptosis of glioma cells to regulate tumor progression. Our results indicated that SLC1A5 is aberrantly expressed in most cancer types and closely associated with prognosis. The GSEA results showed that SLC1A5 is involved in immune activation processes and closely related to the infiltration levels of different immune cells in different cancer types. Upon further investigation, we found that SLC1A5 is a suppressor of ferroptosis in glioma, and SLC1A5 knockdown inhibited the proliferation and migration of glioma cells in vitro. In conclusion, we conducted a pancancer analysis of SLC1A5, demonstrated its role as a prognostic biomarker in cancer patients and explored its potential biological functions.

The ATR inhibitor VE-821 increases the sensitivity of gastric cancer cells to cisplatin.

BACKGROUND: Chemoresistance is a common event after cancer chemotherapy, including gastric cancer (GC). Cisplatin has been reported to induce the DNA damage response (DDR), thus leading to chemoresistance. VE-821, a specific inhibitor of ATR, has been proven to suppress a variety of solid malignancies effectively. Our study aimed to explore the effect of VE-821 on enhancing the chemical sensitivity to cisplatin and clarify the potential molecular mechanisms. METHODS: Cell viability and apoptosis of MKN-45 and AGS were measured by CCK8 and flow cytometry assay respectively. Western blotting was used to detect the expression of target proteins. TCGA database was used to analyze the correlation between the ATR expression with the prognosis of GC patients. The viability of GC organoids was detected by Cell Titer Glo (CTG) through luminescence. RESULTS: Cisplatin inhibited the proliferation and induced apoptosis of GC cells with a relatively high IC50 value, and increased the phosphorylation levels of ATR-CHK1 and H2AX. VE-821 achieved the same effects but by downregulating the phosphorylation levels of the ATR-CHK1 pathway. Besides, higher ATR expression in GC tissues was positively correlated with higher pathological stage in GC patients. Interestingly, ATR inhibition reversed cisplatin-induced STAT3 activation and enhanced H2AX levels. Moreover, VE-821 significantly sensitized GC cells to cisplatin, and these two drugs had synergistic effects in GC cell lines, organoids, and in vivo. CONCLUSION: Our results suggested VE-821 sensitized GC cells to cisplatin via reversing DDR activation. And VE-821 treatment may be a promising therapeutic strategy for GC patients with cisplatin resistance.

Preoperative radiomic signature based on CT images for noninvasive evaluation of localized nephroblastoma in pediatric patients.

Background: Nephron sparing nephrectomy may not reduce the prognosis of nephroblastoma in the absence of involvement of the renal capsule, sinus vessels, and lymph nodes, However, there is no accurate preoperative noninvasive evaluation method at present. Materials and methods: 105 nephroblastoma patients underwent contrast-enhanced CT scan between 2013 and 2020 in our hospital were retrospectively collected, including 59 cases with localized stage and 46 cases with non-localized stage, and then were divided into training cohort (n= 73) and validation cohort (n= 32) according to the order of CT scanning time. After lesion segmentation and data preprocessing, radiomic features were extracted from each volume of interest. The multi-step procedure including Pearson correlation analysis and sequential forward floating selection was performed to produce radiomic signature. Prediction model was constructed using the radiomic signature and Logistic Regression classifier for predicting the localized nephroblastoma in the training cohort. Finally, the model performance was validated in the validation cohort. Results: A total of 1652 radiomic features have been extracted, from which TOP 10 features were selected as the radiomic signature. The area under the receiver operating characteristic curve, accuracy, sensitivity and specificity of the prediction model were 0.796, 0.795, 0.732 and 0.875 for the training cohort respectively, and 0.710, 0.719, 0.611 and 0.857 for the validation cohort respectively. The result comparison with prediction models composed of different machine learning classifiers and different parameters also manifest the effectiveness of our radiomic model. Conclusion: A logistic regression model based on radiomic features extracted from preoperative CT images had good ability to noninvasively predict nephroblastoma without renal capsule, sinus vessel, and lymph node involvement.

Surveillance, Epidemiology, and End Results database and propensity score matching analysis of postoperative radiotherapy for non-malignant meningioma: A retrospective cohort study.

BACKGROUND: The clinical effect of postoperative radiotherapy (PORT) in non-malignant meningioma (NMM) has not been well explored. METHODS: A total of 8629 patients with NMM (surgery alone group: n = 7716, postoperative radiotherapy group: n = 913) were obtained from the Surveillance, Epidemiology, and End Results database. Patient profiles were matched by 1:1 propensity score matching (PSM). Logistic regression analysis was performed to identify factors associated with PORT versus surgery alone (SA). Univariate and multivariate Cox regression analyses determined prognostic variables with overall survival (OS) in NMM. Subgroup analyses were performed with Cox proportional hazards regression models. RESULTS: All the SA (n = 7716) and PORT (n = 913) groups were included. Women with PORT (66.3%) and SA (70.9%) were almost twice as likely as men, and tumors with benign behaviors in the SA group were almost seven times more frequent than those with malignant characteristics. We explored the demographic, clinical characteristics, and prognostic factors in NMM. Laterality, surgery, tumor size, diagnosis year, age, and tumor behavior were associated with PORT versus SA. Patients treated with PORT had better OS than those treated with SA (p = 0.03). After PSM, PORT remained comparable to SA (hazard ratio 0.56, 95% confidence interval 0.35-0.88, p = 0.013). In the subgroup analysis of PORT treatment, borderline malignant behavior increased the death risk by 23%, while other variables did not have a significant clinical benefit (p > 0.05). CONCLUSIONS: Borderline malignant behavior should be considered seriously, and the PORT regimen should be actively implemented for patients with benign meningiomas.

Application of amide proton transfer imaging to pretreatment risk stratification of childhood neuroblastoma: comparison with neuron-specific enolase.

Background: The diagnosis and treatment of childhood neuroblastoma (NB) varies with different risk groups, thus requiring accurate preoperative risk assessment. This study aimed to verify the feasibility of amide proton transfer (APT) imaging in risk stratification of abdominal NB in children, and compare it with the serum neuron-specific enolase (NSE). Methods: This prospective study enrolled 86 consecutive pediatric volunteers with suspected NB, and all subjects underwent abdominal APT imaging on a 3T magnetic resonance imaging scanner. A 4-pool Lorentzian fitting model was used to mitigate motion artifacts and separate the APT signal from the contaminating ones. The APT values were measured from tumor regions delineated by two experienced radiologists. The one-way analysis of variance, independent-sample t-test, Mann-Whitney U-test, and receiver operating characteristic analysis were performed to evaluate and compare the risk stratification performance of the APT value and serum NSE index-a routine biomarker of NB in clinics. Results: Thirty-four cases (mean age, 38.6±32.4 months; 5 very-low-risk, 5 low-risk, 8 intermediate-risk and 16 high-risk ones) were included in the final analysis. The APT values were significantly higher in high-risk NB (5.80%±1.27%) than in the non-high-risk group (3.88%±1.01%) composed of the other three risk groups (P<0.001). However, there was no significant difference (P=0.18) in NSE levels between the high-risk (93.05±97.14 ng/mL) and non-high-risk groups (41.45±30.99 ng/mL). The associated area under the curve (AUC) of the APT parameter (AUC =0.89) in differentiating high-risk NB from non-high-risk NB was significantly higher (P=0.03) than that of NSE (AUC =0.64). Conclusions: As an emerging non-invasive magnetic resonance imaging technique, APT imaging has a promising prospect for distinguishing high-risk NB from non-high-risk NB in routine clinical applications.

Radiomic-based machine learning model for predicting the surgical risk in children with abdominal neuroblastoma.

Background: Preoperative imaging assessment of surgical risk is very important for the prognosis of these children. To develop and validate a radiomics-based machine learning model based on the analysis of radiomics features to predict surgical risk in children with abdominal neuroblastoma (NB). Methods: A retrospective study was conducted from April 2019 to March 2021 among 74 children with abdominal NB. A total of 1874 radiomic features in MR images were extracted from each patient. Support vector machines (SVMs) were used to establish the model. Eighty percent of the data were used as the training set to optimize the model, and 20% of the data were used to validate its accuracy, sensitivity, specificity and area under the curve (AUC) to verify its effectiveness. Results: Among the 74 children with abdominal NB, 55 (65%) had surgical risk and 19 (35%) had no surgical risk. A t test and Lasso identified that 28 radiomic features were associated with surgical risk. After developing an SVM-based model using these features, predictions were made about whether children with abdominal NB had surgical risk. The model achieved an AUC of 0.94 (a sensitivity of 0.83 and a specificity of 0.80) with 0.890 accuracy in the training set and an AUC of 0.81 (a sensitivity of 0.73 and a specificity of 0.82) with 0.838 accuracy in the test set. Conclusions: Radiomics and machine learning can be used to predict the surgical risk in children with abdominal NB. The model based on 28 radiomic features established by SVM showed good diagnostic efficiency.

Clinical diagnosis model of spinal meningiomas based on the surveillance, epidemiology, and end results database.

Most spinal meningiomas (SM) are benign lesions of the thoracic spine and are usually treated surgically. This study aimed to explore treatment strategies and construct a nomogram for SM. Data on patients with SM from 2000 to 2019 were extracted from the Surveillance, Epidemiology, and End Results database. First, the distributional properties and characteristics of the patients were descriptively evaluated, and the patients were randomly divided into training and testing groups in a 6:4 ratio. Least absolute shrinkage and selection operator (LASSO) regression was used to screen the survival predictors. Kaplan-Meier curves explained survival probability by different variables. The nomogram was constructed based on the results of LASSO regression. The predictive power of the nomogram was identified using the concordance index, time-receiver operating characteristics, decision curve analysis, and calibration curves. We recruited 1,148 patients with SM. LASSO results for the training group showed that sex (coefficient, 0.004), age (coefficient, 0.034), surgery (coefficient, -0.474), tumor size (coefficient, 0.008), and marital status (coefficient, 0.335) were prognostic factors. The nomogram prognostic model showed good diagnostic ability in both the training and testing groups, with a C-index of 0.726, 95% (0.679, 0.773); 0.827, 95% (0.777, 0.877). The calibration and decision curves suggested that the prognostic model had better diagnostic performance and good clinical benefit. In the training and testing groups, the time-receiver operating characteristic curve showed that SM had moderate diagnostic ability at different times, and the survival rate of the high-risk group was significantly lower than that of the low-risk group (training group: p = 0.0071; testing group: p = 0.00013). Our nomogram prognostic model may have a crucial role in predicting the six-month, one-year, and two-year survival outcomes of patients with SM and may be useful for surgical clinicians to formulate treatment plans.

Smart Phototheranostics based on Carbon Nanohorns for Precise Imaging-Guided Post-PDT toward Residual Tumor Cells after Initial Phototherapy.

As promising photonic material, phototheranostics can be activated in the laser irradiation range of tumor with sensitivity and spatiotemporal precision. However, it is difficult to completely eradicate solid tumors due to their irregularity and limited laser irradiation area. Herein, multi-stimulus responsive HA-Ce6@SWNHs were constructed with single-walled carbon nanohorns (SWNHs) and chlorine e6 (Ce6) modified hyaluronic acid (HA) via non-covalent binding. This SWNHs-based phototheranostics not only exhibited water dispersion but also could target tumor and be activated by near-infrared light for photodynamic therapy (PDT) and photothermal therapy (PTT). Additionally, HA-Ce6@SWNHs could be degraded by hyaluronidase in residual tumor cells, causing HA-Ce6 to fall off the SWNHs surfaces to restore autofluorescence, thus precisely guiding the programmed photodynamic treatments for residual tumor cells after the initial phototherapy. Thus, this work provides a rationally designed multiple-stimulus-response strategy to develop smart SWNHs-based phototheranostics for precise PDT/PTT and post-treatment imaging-guided PDT of residual tumor cells.

An enriched ammonia-oxidizing microbiota enables high removal efficiency of ammonia in antibiotic production wastewater.

High ammonia concentration hinders the efficient treatment of antibiotic production wastewater (APW). Developing effective ammonia oxidation wastewater treatment strategies is an ideal approach for facilitating APW treatment. Compared with traditional nitrification strategies, the partial nitrification process is more eco-friendly, less energy-intensive, and less excess sludge. The primary limiting factor of the partial nitrification process is increasing ammonia-oxidizing bacteria (AOB) while decreasing nitrite-oxidizing bacteria (NOB). In this study, an efficient AOB microbiota (named AF2) was obtained via enrichment of an aerobic activated sludge (AS0) collected from a pharmaceutical wastewater treatment plant. After a 52-day enrichment of AS0 in 250 mL flasks, the microbiota AE1 with 69.18% Nitrosomonas microorganisms was obtained. Subsequent scaled-up cultivation in a 10 L fermenter led to the AF2 microbiota with 59.22% Nitrosomonas. Low concentration of free ammonia (FA, < 42.01 mg L-1) had a negligible effect on the activity of AF2, and the nitrite-nitrogen accumulation rate (NAR) of AF2 was 98% when FA concentration was 42.01 mg L-1. The specific ammonia oxidation rates (SAORs) at 30 °C and 15 °C were 3.64 kg NH4+-N·kg MLVSS-1·d-1 and 1.43 kg NH4+-N·kg MLVSS-1·d-1 (MLVSS: mixed liquor volatile suspended solids). The SAOR was 0.52 kg NH4+-N·kg MLVSS-1·d-1 when the NaCl concentration was increased from 0 to 20 g L-1, showing that AF2 functioning was stable in a high-level salt environment. The ammonia oxidation performance of AF2 was verified by treating abamectin and lincomycin production wastewater. The NARs of AF2 used for abamectin and lincomycin production wastewater treatment were >90% and the SAORs were 2.39 kg NH4+-N·kg MLVSS-1·d-1 and 0.54 kg NH4+-N·kg MLVSS-1·d-1, respectively, which was higher than the traditional biological denitrification process. In summary, AF2 was effective for APW treatment via enhanced ammonia removal efficiency, demonstrating great potential for future industrial wastewater treatment.

Pirfenidone-loaded exosomes derived from pancreatic ductal adenocarcinoma cells alleviate fibrosis of premetastatic niches to inhibit liver metastasis.

Given the metastasis-promoting effect of pancreatic ductal adenocarcinoma (PDAC)-derived exosomes through activation of fibrotic premetastatic niches, targeting and intervening in premetastatic organs to inhibit distant metastasis have challenged researchers and clinicians. Herein, a self-biomimetic drug delivery system based on exosomes derived from PDAC (PF@PCCEs) was constructed to precisely deliver an antifibrotic drug (pirfenidone, PF) to fibrotic premetastatic organs. First, PDAC-derived exosomes were confirmed to remarkably promote liver fibrosis. Then the prepared PF@PCCEs were actively internalized by HSCs (hepatic stellate cells) and subsequently alleviated the activation of HSCs. Delivery of PF to the premetastatic liver affected the niche suitable for the colonization of circulating tumour cells, further suppressing liver metastasis of PDAC. Thus, the strategy for intervening in the formation of fibrotic premetastatic niches to inhibit liver metastasis of PDAC using PF@PCCEs might offer inspiration for the treatment of tumour metastasis.

CIP2A deficiency promotes depression-like behaviors in mice through inhibition of dendritic arborization.

Major depressive disorder (MDD) is a severe mental illness. Decreased brain plasticity and dendritic fields have been consistently found in MDD patients and animal models; however, the underlying molecular mechanisms remain to be clarified. Here, we demonstrate that the deletion of cancerous inhibitor of PP2A (CIP2A), an endogenous inhibitor of protein phosphatase 2A (PP2A), leads to depression-like behaviors in mice. Hippocampal RNA sequencing analysis of CIP2A knockout mice shows alterations in the PI3K-AKT pathway and central nervous system development. In primary neurons, CIP2A stimulates AKT activity and promotes dendritic development. Further analysis reveals that the effect of CIP2A in promoting dendritic development is dependent on PP2A-AKT signaling. In vivo, CIP2A deficiency-induced depression-like behaviors and impaired dendritic arborization are rescued by AKT activation. Decreased CIP2A expression and impaired dendrite branching are observed in a mouse model of chronic unpredictable mild stress (CUMS). Indicative of clinical relevance to humans, CIP2A expression is found decreased in transcriptomes from MDD patients. In conclusion, we discover a novel mechanism that CIP2A deficiency promotes depression through the regulation of PP2A-AKT signaling and dendritic arborization.

Single-walled carbon nanohorns-based smart nanotheranostic: From phototherapy to enzyme-activated fluorescence imaging-guided photodynamic therapy.

Phototheranostics, a local non-invasive approach that integrates light-based diagnostics and therapeutics, enables precise treatment using nanotheranostic agents with minimal damage to normal tissues. However, ensuring high-efficiency ablation of cancer cells using phototheranostics for one time irradiation is highly challenging. Herein, we designed and synthesized a single-walled carbon nanohorns-based nanotheranostic agent, HA-IR808-SWNHs, by loading IR808, a photosensitizer, conjugated hyaluronic acid (HA) with an amide bond on the surface of single-walled carbon nanohorns (SWNHs) through noncovalent π-π interaction by the sonication method. The HA in HA-IR808-SWNHs improves the water dispersibility of SWNHs and endows SWNHs with targeting capabilities. Importantly, overexpressed endogenous hyaluronidase in cancer cells actively disassembles HA-IR808-SWNHs, forming small HA-IR808 fragments. The fragments exhibit a strong fluorescence signal and can be used to guide programmed photodynamic therapy for sequentially eliminating the residual living cancer cells. The current study confirms that HA-IR808-SWNHs is an endogenous enzyme-responsive nanotheranostic agent that can be employed to precisely track and ablate residual cancer cells in a spatiotemporal manner. The results strengthen the understanding of SWNH functionalization and expand its potential biomedical application, especially in cancer theranostics.

Predicting MGMT Promoter Methylation in Diffuse Gliomas Using Deep Learning with Radiomics.

This study aimed to investigate the feasibility of predicting oxygen 6-methylguanine-DNA methyltransferase (MGMT) promoter methylation in diffuse gliomas by developing a deep learning approach using MRI radiomics. A total of 111 patients with diffuse gliomas participated in the retrospective study (56 patients with MGMT promoter methylation and 55 patients with MGMT promoter unmethylation). The radiomics features of the two regions of interest (ROI) (the whole tumor area and the tumor core area) for four sequences, including T1 weighted image (T1WI), T2 weighted image (T2WI), apparent diffusion coefficient (ADC) maps, and T1 contrast-enhanced (T1CE) MR images were extracted and jointly fed into the residual network. Then the deep learning method was developed and evaluated with a five-fold cross-validation, where in each fold, the dataset was randomly divided into training (80%) and validation (20%) cohorts. We compared the performance of all models using area under the curve (AUC) and average accuracy of validation cohorts and calculated the 10 most important features of the best model via a class activation map. Based on the ROI of the whole tumor, the predictive capacity of the T1CE and ADC model achieved the highest AUC value of 0.85. Based on the ROI of the tumor core, the T1CE and ADC model achieved the highest AUC value of 0.90. After comparison, the T1CE combined with the ADC model based on the ROI of the tumor core exhibited the best performance, with the highest average accuracy (0.91) and AUC (0.90) among all models. The deep learning method using MRI radiomics has excellent diagnostic performance with a high accuracy in predicting MGMT promoter methylation in diffuse gliomas.

Machine Learning-Based CT Radiomics Method for Identifying the Stage of Wilms Tumor in Children.

Purpose: To develop and validate a machine learning-based CT radiomics method for preoperatively predicting the stages (stage I and non-stage I) of Wilms tumor (WT) in pediatric patients. Methods: A total of 118 patients with WT, who underwent contrast-enhanced computed tomography (CT) scans in our center between 2014 and 2021, were studied retrospectively and divided into two groups: stage I and non-stage I disease. Patients were randomly divided into training cohorts (n = 94) and test cohorts (n = 24). A total of 1,781 radiomic features from seven feature classes were extracted from preoperative portal venous-phase images of abdominal CT. Synthetic Minority Over-Sampling Technique (SMOTE) was used to handle imbalanced datasets, followed by a t-test and Least Absolute Shrinkage and Selection Operator (LASSO) regularization for feature selection. Support Vector Machine (SVM) was deployed using the selected informative features to develop the predicting model. The performance of the model was evaluated according to its accuracy, sensitivity, and specificity. The receiver operating characteristic curve (ROC) and the area under the ROC curve (AUC) was also arranged to assess the model performance. Results: The SVM model was fitted with 15 radiomic features obtained by t-test and LASSO concerning WT staging in the training dataset and demonstrated favorable performance in the testing dataset. Cross-validated AUC on the training dataset was 0.79 with a 95 percent confidence interval (CI) of 0.773-0.815 and a coefficient of variation of 3.76%, while AUC on the test dataset was 0.81, and accuracy, sensitivity, and specificity were 0.79, 0.87, and 0.69, respectively. Conclusions: The machine learning model of SVM based on radiomic features extracted from CT images accurately predicted WT stage I and non-stage I disease in pediatric patients preoperatively, which provided a rapid and non-invasive way for investigation of WT stages.