Single-cell transcriptomic sequencing data reveal aberrant DNA methylation in SMAD3 promoter region in tumor-associated fibroblasts affecting molecular mechanism of radiosensitivity in non-small cell lung cancer.

OBJECTIVE: Non-small cell lung cancer (NSCLC) often exhibits resistance to radiotherapy, posing significant treatment challenges. This study investigates the role of SMAD3 in NSCLC, focusing on its potential in influencing radiosensitivity via the ITGA6/PI3K/Akt pathway. METHODS: The study utilized gene expression data from the GEO database to identify differentially expressed genes related to radiotherapy resistance in NSCLC. Using the GSE37745 dataset, prognostic genes were identified through Cox regression and survival analysis. Functional roles of target genes were explored using Gene Set Enrichment Analysis (GSEA) and co-expression analyses. Gene promoter methylation levels were assessed using databases like UALCAN, DNMIVD, and UCSC Xena, while the TISCH database provided insights into the correlation between target genes and CAFs. Experiments included RT-qPCR, Western blot, and immunohistochemistry on NSCLC patient samples, in vitro studies on isolated CAFs cells, and in vivo nude mouse tumor models. RESULTS: Fifteen key genes associated with radiotherapy resistance in NSCLC cells were identified. SMAD3 was recognized as an independent prognostic factor for NSCLC, linked to poor patient outcomes. High expression of SMAD3 was correlated with low DNA methylation in its promoter region and was enriched in CAFs. In vitro and in vivo experiments confirmed that SMAD3 promotes radiotherapy resistance by activating the ITGA6/PI3K/Akt signaling pathway. CONCLUSION: High expression of SMAD3 in NSCLC tissues, cells, and CAFs is closely associated with poor prognosis and increased radiotherapy resistance. SMAD3 is likely to enhance radiotherapy resistance in NSCLC cells by activating the ITGA6/PI3K/Akt signaling pathway.

A case of colonic muco-submucosal elongated polyp (CMSEP) misdiagnosed as a inverted colonic diverticulum (ICD).

CMSEP is a large intestine polyp with a long and broad stalk and a "worm-like" appearance which is covered by normal mucosa. The submucosal layer consists of edematous and fibrotic interstitium, adipose tissue, dilated blood vessels, and lymphatic follicles[1]. Endoscopic magnification of the mucosal surface showed a uniform honeycomb pattern of regular blood vessels, with soft and deformable "folds" and "gyrus" at the top. The exact pathogenesis of CMSEP is still unclear.

Study of enhanced radiofrequency heating by pre-freezing tissue.

In our previous animal model study, we found that radiofrequency (RF) ablation of pre-frozen tumor resulted in improved therapeutic effects. To understand the underlying mechanisms and optimize the treatment protocol, the RF heating pattern in pre-frozen tissue was studied in this paper. Both ex vivo and in vivo experiments were conducted to compare the temperature profiles of RF heating with or without pre-freezing. Results showed that the heating rate of in vivo tissues was significantly higher with pre-freezing. However, little difference was observed in the heating rate of ex vivo tissues with or without pre-freezing. In the histopathologic analysis of in vivo tissues, both a larger ablation area and a wider transitional zone were found in the tissue with pre-freezing. To investigate the cause for the enhancement in RF heating, the parameters affecting the tissue temperature rise were studied. It was found that the electrical conductivity of in vivo tissue with pre-freezing was much higher at low frequencies, but little difference was found at the 460 kHz frequency commonly used in clinical applications. A finite element model for RF heating was developed and validated to fit the thermal conductivity of in vivo tissue including effects of pre-freezing and the associated blood perfusion rate. Results showed that the enhancement of the heating rate was primarily attributed to the decreased blood perfusion rate in the tissue with vascular damage caused by pre-freezing. The ablation volume was increased by 104% due to the reduced heat dissipation.

Targeting Nrf2/PHKG2 axis to enhance radiosensitivity in NSCLC.

While ferroptosis shows promise in anti-cancer strategy, the molecular mechanisms behind this process remain poorly understood. Our research aims to highlight the regulation of radiotherapy-induced ferroptosis in non-small cell lung cancer (NSCLC) via the NRF2/PHKG2 axis-mediated mechanism. To identify ferroptosis-associated genes associated with radioresistance in NSCLC, this study employed high-throughput transcriptome sequencing and Lasso risk regression analysis. Clinical samples were analyzed to confirm PHKG2 expression changes before and after radiotherapy. The study further examined ferritinophagy-related factors, intracellular iron levels, mitochondrial function, and ferroptosis in NSCLC cells undergoing radiation exposure to explore the effect of PHKG2 on radiosensitivity or radioresistance. The research also demonstrated the transcriptional inhibition of PHKG2 by NRF2 and created in situ transplantation tumor models of NSCLC to examine the role of NRF2/PHKG2 axis in NSCLC radiosensitivity and resistance in vivo. The Lasso risk regression model that incorporated ferroptosis-associated genes effectively predicted the prognosis of patients with NSCLC. Radiotherapy-sensitive tissues exhibited an increased expression of PHKG2. Overexpression of PHKG2 led to elevated intracellular iron levels by promoting ferritinophagy and increased mitochondrial stress-dependent ferroptosis induced by radiotherapy. PHKG2 transcription repression was achieved through NRF2. The FAGs-Lasso risk regression model can accurately predict the prognosis of NSCLC patients. Targeting Nrf2 upregulates the expression of PHKG2 and reverses radiotherapy resistance in NSCLC by promoting iron autophagy and inducing mitochondrial dysfunction, thereby increasing radiotherapy sensitivity.

Mesenchymal stem cells overexpressing XIST induce macrophage M2 polarization and improve neural stem cell homeostatic microenvironment, alleviating spinal cord injury.

Spinal cord injury (SCI) is a significant cause of disability worldwide, with limited treatment options. This study investigated the potential of bone marrow-derived mesenchymal stem cells (BMSCs) modified with XIST lentiviral vector to modulate macrophage polarization and affect neural stem cell (NSC) microenvironment reconstruction following SCI. Bioinformatics analysis revealed that MID1 might be crucial for BMSCs' treatment of SCI. XIST overexpression enriched Zmynd8 to the promoter region of MID1 and inhibited MID1 transcription, which promoted macrophage M2 polarization. In vitro experiments showed that BMSCs-XIST promoted NSC proliferation, migration, differentiation, and axonal growth by inducing macrophage M2 polarization, suppressing inflammation, and accelerating the re-establishment of the homeostatic microenvironment of NSCs. In vivo, animal experiments confirmed that BMSCs-XIST significantly alleviated SCI by promoting NSC differentiation and axon formation in the injured area. The study demonstrated the potential of XIST-overexpressing BMSCs for treating SCI by regulating macrophage polarization and homeostasis of the NSC microenvironment. These findings provide new insights into the development of stem cell-based therapies for SCI.

Research progress of brain organoids in the field of diabetes.

Human embryonic stem cells and human induced pluripotent stem cells may be used to create 3D tissues called brain organoids. They duplicate the physiological and pathological characteristics of human brain tissue more faithfully in terms of both structure and function, and they more precisely resemble the morphology and cellular structure of the human embryonic brain. This makes them valuable models for both drug screening and in vitro studies on the development of the human brain and associated disorders. The technical breakthroughs enabled by brain organoids have a significant impact on the research of different brain regions, brain development and sickness, the connections between the brain and other tissues and organs, and brain evolution. This article discusses the development of brain organoids, their use in diabetes research, and their progress.

Outcome Prediction of Spontaneous Supratentorial Intracerebral Hemorrhage after Surgical Treatment Based on Non-Contrast Computed Tomography: A Multicenter Study.

This study aims to explore the value of a machine learning (ML) model based on radiomics features and clinical features in predicting the outcome of spontaneous supratentorial intracerebral hemorrhage (sICH) 90 days after surgery. A total of 348 patients with sICH underwent craniotomy evacuation of hematoma from three medical centers. One hundred and eight radiomics features were extracted from sICH lesions on baseline CT. Radiomics features were screened using 12 feature selection algorithms. Clinical features included age, gender, admission Glasgow Coma Scale (GCS), intraventricular hemorrhage (IVH), midline shift (MLS), and deep ICH. Nine ML models were constructed based on clinical feature, and clinical features + radiomics features, respectively. Grid search was performed on different combinations of feature selection and ML model for parameter tuning. The averaged receiver operating characteristics (ROC) area under curve (AUC) was calculated and the model with the largest AUC was selected. It was then tested using multicenter data. The combination of lasso regression feature selection and logistic regression model based on clinical features + radiomics features had the best performance (AUC: 0.87). The best model predicted an AUC of 0.85 (95%CI, 0.75-0.94) on the internal test set and 0.81 (95%CI, 0.64-0.99) and 0.83 (95%CI, 0.68-0.97) on the two external test sets, respectively. Twenty-two radiomics features were selected by lasso regression. The second-order feature gray level non-uniformity normalized was the most important radiomics feature. Age is the feature with the greatest contribution to prediction. The combination of clinical features and radiomics features using logistic regression models can improve the outcome prediction of patients with sICH 90 days after surgery.

Aorticoesophagal Fistula Combined with Upper Gastrointestinal Bleeding after Endovascular Dissection of Thoracic Aortic Aneurysm.

Aortoesophageal fistula (AEF) is a relatively rare and potentially fatal disease. Secondary AEF is rare but is associated with serious complications and high mortality. There are rare cases of esophageal mediastinal fistula after descending aortic aneurysm stent implantation. We report the case of a 76-year-old man who had upper abdominal distension, without obvious inducement, for 3 months and felt fullness after a meal, accompanied by anorexia. A chest computer tomography (CT) examination of the abdomen was performed with the outside hospital. Descending thoracic aortic aneurysm was discovered and was treated with stent implantation. The patient was transferred to our hospital to continue treatment, mainly because of an esophageal mediastinal fistula. Finally, the thoracic aortic aneurysm was diagnosed as AEF after stent implantation, combined with the diagnosis of upper gastrointestinal bleeding. We hope that, through this case, we can explain the possible causes of bronchial mediastinal fistula after stent implantation of descending aortic aneurysm and the mechanism of upper gastrointestinal bleeding.

A Novel Tumor Progression Prediction Method for Multimode Ablation Treatment.

OBJECTIVE: The multimode ablation of liver cancer, which uses radio-frequency heating after a pre-freezing process to treat the tumor, has shown significantly improved therapeutic effects and enhanced anti-tumor immune response. Unlike open surgery, the ablated lesions remain in the body after treatment, so it is critical to assess the immediate outcome and to monitor disease status over time. Here we propose a novel tumor progression prediction method for simultaneous postoperative evaluation and prognosis analysis. METHODS: We propose to leverage the intraoperative therapeutic information extracted from thermal dose distribution. For tumors with specific sensitivity reflected in medical images, different thermal doses implicitly indicate the degree of instant damage and long-term inhibition excited under specific ablation energy. We further propose a survival analysis framework for the multimode ablation treatment. It extracts carefully designed features from clinical, preoperative, intraoperative, and postoperative data, then uses random survival forest for feature selection and deep neural networks for survival prediction. RESULTS: We evaluated the proposed methods using clinical data. The results show that our method outperforms the state-of-the-art survival analysis methods with a C-index of 0.855±0.090. The thermal dose information contributes significantly to the prediction accuracy by taking up 21.7% of the overall feature importance. CONCLUSION: The proposed methods have been demonstrated to be a powerful tool in tumor progression prediction of multimode ablation therapy. SIGNIFICANCE: This kind of data-driven prognosis analysis may benefit personalized medicine and simplify the follow-up process.

Risk factors for poor outcomes of spontaneous supratentorial cerebral hemorrhage after surgery.

OBJECTIVE: This study aimed to explore the factors affecting the outcomes of spontaneous supratentorial cerebral hemorrhage 90 days after surgery. METHODS: A total of 256 patients with spontaneous supratentorial intracerebral hemorrhage underwent craniotomy evacuation of hematoma. The control group included 120 patients who received conservative treatment. The patients were divided into two subgroups based on a bifurcation of the modified Rankin Scale (mRS) 90 days after clinical therapeutics: good outcome (mRS score 0-3) and poor outcome (mRS score 4-6). The differences in clinical and imaging data between the two subgroups were analyzed. Based on difference analysis results, a binary logistic regression model was constructed to analyze the influencing factors related to poor outcomes. RESULTS: The difference analysis results in the surgery group showed statistically significant differences in age, sex, Glasgow Coma Score (GCS) on admission, coronary atherosclerosis, smoking, stroke history, blood glucose, D-dimer, hematoma size, deep cerebral hemorrhage, midline shift, hematoma burst into the ventricle, vortex sign, island sign, and black hole sign. Binary logistic regression analysis showed that deep cerebral hemorrhage, midline shift, and age > 58 years independently correlated with the poor outcomes of patients after surgery. The binary logistic regression results of the control group showed that age > 58 years and GCS ≤ 8 independently correlated with the poor outcomes of patients. CONCLUSIONS: Deep cerebral hemorrhage, midline shift, and age > 58 years significantly increased the risk of adverse prognosis in patients after surgery. The findings might help select the clinical treatment plan and evaluate the postoperative prognosis of patients.

A Novel Multi-Mode Thermal Therapy for Colorectal Cancer Liver Metastasis: A Pilot Study.

A novel multi-mode thermal therapy was developed for local tumor ablation and the systemic stimulation of anti-tumor immunity, consisting of a rapid liquid nitrogen freezing, and followed by the radiofrequency heating of target tumor tissue. This pilot study aimed to compare the therapeutic effects of the new therapy with conventional radiofrequency ablation (RFA) on patients with colorectal cancer liver metastasis (CRCLM). From August 2016 to September 2019, thirty-one patients with CRCLM received either multi-mode thermal therapy (n = 17) or RFA (n = 14). Triphasic contrast-enhanced magnetic resonance imaging (MRI), routine blood tests, and peripheral blood immune responses were evaluated before the treatment and in 1, 3, 6, and 12 months after. Local tumor response and progression-free survival (PFS) were assessed using the Kaplan-Meier method, and pre- and post-treatment immune cell counts were analyzed using Mann-Whitney U and Wilcoxon tests. A significantly longer PFS was observed in the multi-mode thermal therapy group in comparison to that of the conventional RFA group (median, 11.4 versus 3.4 months, p = 0.022). It was found that multi-mode therapy induced the functional maturation of dendritic cells, promoted CD4+ T cell-mediated antitumor responses, and decreased regulatory T cells, contributing to better therapeutic efficacy in CRCLM patients.

Improvement of resistive switching characteristics in ZrO2 film by embedding a thin TiOx layer.

The stabilization of the resistive switching characteristics is important to resistive random access memory (RRAM) device development. In this paper, an alternative approach for improving resistive switching characteristics in ZrO(2)-based resistive memory devices has been investigated. Compared with the Cu/ZrO(2)/Pt structure device, by embedding a thin TiO(x) layer between the ZrO(2) and the Cu top electrode, the Cu/TiO(x)-ZrO(2)/Pt structure device exhibits much better resistive switching characteristics. The improvement of the resistive switching characteristics in the Cu/TiO(x)-ZrO(2)/Pt structure device might be attributed to the modulation of the barrier height at the electrode/oxide interfaces.

Prediction of Progression to Severe Stroke in Initially Diagnosed Anterior Circulation Ischemic Cerebral Infarction.

Purpose: Accurate prediction of the progression to severe stroke in initially diagnosed nonsevere patients with acute-subacute anterior circulation nonlacuna ischemic infarction (ASACNLII) is important in making clinical decision. This study aimed to apply a machine learning method to predict if the initially diagnosed nonsevere patients with ASACNLII would progress to severe stroke by using diffusion-weighted images and clinical information on admission. Methods: This retrospective study enrolled 344 patients with ASACNLII from June 2017 to August 2020 on admission, and 108 cases progressed to severe stroke during hospitalization within 3-21 days. The entire data were randomized into a training set (n = 271) and an independent test set (n = 73). A U-Net neural network was employed for automatic segmentation and volume measurement of the ischemic lesions. Predictive models were developed and used for evaluating the progression to severe stroke using different feature sets (the volume data, the clinical data, and the combination) and machine learning methods (random forest, support vector machine, and logistic regression). Results: The U-Net showed high correlation with manual segmentation in terms of Dice coefficient of 0.806 and R 2 value of the volume measurements of 0.960 in the test set. The random forest classifier of the volume + clinical combination achieved the best area under the receiver operating characteristic curve of 0.8358 (95% CI 0.7321-0.9269), and the accuracy, sensitivity, and specificity were 0.7780 (0.7397-0.7945), 0.7695 (0.6102-0.9074), and 0.8686 (0.6923-1.0), respectively. The Shapley additive explanation diagram showed the volume variable as the most important predictor. Conclusion: The U-Net was fully automatic and showed a high correlation with manual segmentation. An integrated approach combining clinical variables and stroke lesion volumes that were derived from the advanced machine learning algorithms had high accuracy in predicting the progression to severe stroke in ASACNLII patients.

A New Model for Estimation of Individual Blood Flow Effect during Multimode Thermal Therapy of Tumor.

An accurate temperate control is the key during multimode thermal therapy of tumor. However, the tumor tissue temperature is greatly influenced by local blood flow changes of individuals. A simple but effective method is proposed for estimation of the local blood flow and its impact on the ablation boundary temperature. The proposed model is focused on the tumor domain, namely the targeted treatment region. In the natural thawing process post tumor freezing during the therapy, the main energy transferring to the tumor tissue comes from the blood flow of the surrounding normal tissue on the tumor boundary. By fitting the rewarming temperature measured in the tissue, the inversed problem is solved by the model to calculate the boundary convection condition and thus to predict the corresponding blood perfusion rate. The model is validated by the animal experimental data. The calculated blood perfusion rates are within the published range, but differ individually. The results prove that the new model and the estimated personalized convection coefficient can better predict the tissue temperature distribution during the therapy.Clinical Relevance-The model estimates the local blood flows around the tumor of individuals and the influence on heat transfer process. It can be used to better predict and control the temperature on the tumor boundary during the therapy that is critical to the therapeutic effect. The model also greatly cuts down the calculation time which facilitates the possibility of intraoperative real time monitoring.

An Noninvasive and Impedance-Ignored Control Strategy of the Ablation Zone in Radiofrequency Ablation Therapy.

This study proposed a control strategy of the ablation margin using the temperature of the probe, without causing additional damage. Compared with other methods, the proposed strategy is real time and impedance-ignored, thus has a better performance in practice. A theoretical model was established to obtain the temperature distribution during the treatment. Several functions were obtained by fitting the results of the simulation model, with which a preset central temperature curve corresponding to a desired ablation zone was determined to regulate the temperature of the control point. Considering the various impedances in practice, a voltage adjustment method according to the error between the preset central temperature and the practical central temperature was proposed to minimize the effect of impedances. At last, the strategy was verified with phantom experiments. The results show that all the temperatures of the control points reached to 50°C at a specific time and kept for a while, which demonstrated the strategy had a good performance within the error range allowed.

A New Model for RF Ablation Planning in Clinic.

Numerical simulations provide effective way to acquire detailed temperature field during radiofrequency ablation (RF). Based on the patient's real electrical resistance and RF power, we have designed a theoretical model suitable for clinical treatment planning. The human body is assumed to be two cylinders with the inner cylinder simulating the liver with real liver electrical conductivity, while the electrical conductivity of the out cylinder adjusted to match the real resistance recorded when treated with RFA. The orthogonal-array method has been applied to analyze the impact of the main geometric parameters. Results show that a limited range of model parameters with the same resistance and power condition results in similar prediction of ablation range. In addition, RF heating experiments have been performed in the liver of a live pig to validate this model. The simulated temperature fits well with the real temperature. The comparison of the results predicted using the proposed model and previous models finds that the previous uniform-electrical-conductivity model would significantly underestimates or overestimates the ablation range based on the magnitude of the electrical resistance recorded.

Theoretical and experimental study of dual-fiber laser ablation for prostate cancer.

Single-fiber laser treatment of the prostate has been widely accepted in the clinic due to its minimal invasiveness and high controllability. However, for large tumors, multiple insertions of the laser probe would be needed to achieve full coverage of the tumor, increasing the complexity of the treatment and occasionally resulting in the incomplete killing of tumor cells due to a mismatch between the planned insertion location and the actual probe insertion location. Treatment with a dual-fiber laser results in greater lesion coverage following a single insertion of the probe, with the lesion coverage being even greater than the sum of the coverage of two sequential insertion of a single-fiber laser probe, potentially reducing treatment time and clinical complications. Both theoretical and experimental analyses have been performed to evaluate the proposed dual-fiber laser treatment. A finite element model was established to simulate the treatment process. The simulation results indicated that there is a clear difference between the ablation coverage created using dual-fiber laser ablation and that created using the superposition of sequential single-fiber laser ablation. In addition, the coverage is dependent on the spacing distance between the two fibers. Both ex vivo and in vivo canine prostate tissues were treated by dual-fiber laser ablation, with lesions analyzed by magnetic resonance imaging (MRI), ultrasound imaging, and pathology. The results demonstrate that dual-fiber laser ablation can markedly increase the range of the ablation zone when compared with single-fiber modes. The safety and feasibility of dual-fiber laser treatment has been confirmed, and a treatment plan using dual-fiber laser ablation has also been proposed.

Bipolar one diode-one resistor integration for high-density resistive memory applications.

Different from conventional unipolar-type 1D-1R RRAM devices, a bipolar-type 1D-1R memory device concept is proposed and successfully demonstrated by the integration of Ni/TiOx/Ti diode and Pt/HfO2/Cu bipolar RRAM cell to suppress the undesired sneak current in a cross-point array. The bipolar 1D-1R memory device not only achieves self-compliance resistive switching characteristics by the reverse bias current of the Ni/TiOx/Ti diode, but also exhibits excellent bipolar resistive switching characteristics such as uniform switching, satisfactory data retention, and excellent scalability, which give it high potentiality for high-density integrated nonvolatile memory applications.