Pancreatic mucinous adenocarcinoma has different clinical characteristics and better prognosis compared to non-specific PDAC: A retrospective observational study.

Background: Pancreatic mucinous adenocarcinoma (PMAC) is a rare malignant tumour, and there is limited understanding of its epidemiology and prognosis. Initially, PMAC was considered a metastatic manifestation of other cancers; however, instances of non-metastatic PMAC have been documented through monitoring, epidemiological studies, and data from the Surveillance, Epidemiology, and End Results (SEER) database. Therefore, it is crucial to investigate the epidemiological characteristics of PMAC and discern the prognostic differences between PMAC and the more prevalent pancreatic ductal adenocarcinoma (PDAC). Methods: The study used data from the SEER database from 2000 to 2018 to identify patients diagnosed with PMAC or PDAC. To ensure comparable demographic characteristics between PDAC and PMAC, propensity score matching was employed. Kaplan-Meier analysis was used to analyse overall survival (OS) and cancer-specific survival (CSS). Univariate and multivariate Cox regression analyses were used to determine independent risk factors influencing OS and CSS. Additionally, the construction and validation of risk-scoring models for OS and CSS were achieved through the least absolute shrinkage and selection operator-Cox regression technique. Results: The SEER database included 84,857 patients with PDAC and 3345 patients with PMAC. Notably, significant distinctions were observed in the distribution of tumour sites, diagnosis time, use of radiotherapy and chemotherapy, tumour size, grading, and staging between the two groups. The prognosis exhibited notable improvement among married individuals, those receiving acceptable chemotherapy, and those with focal PMAC (p < 0.05). Conversely, patients with elevated log odds of positive lymph node scores or higher pathological grades in the pancreatic tail exhibited a more unfavourable prognosis (p < 0.05). The risk-scoring models for OS or CSS based on prognostic factors indicated a significantly lower prognosis for high-risk patients compared to their low-risk counterparts (area under the curve OS: 0.81-0.82, CSS: 0.80-0.82). Conclusion: PMAC exhibits distinct clinical characteristics compared to non-specific PDAC. Leveraging these features and pathological classifications allows for accurate prognostication of PMAC or PDAC.

A novel approach for estimating lung tumor motion based on dynamic features in 4D-CT.

Due to the high expenses involved, 4D-CT data for certain patients may only include five respiratory phases (0%, 20%, 40%, 60%, and 80%). This limitation can affect the subsequent planning of radiotherapy due to the absence of lung tumor information for the remaining five respiratory phases (10%, 30%, 50%, 70%, and 90%). This study aims to develop an interpolation method that can automatically derive tumor boundary contours for the five omitted phases using the available 5-phase 4D-CT data. The dynamic mode decomposition (DMD) method is a data-driven and model-free technique that can extract dynamic information from high-dimensional data. It enables the reconstruction of long-term dynamic patterns using only a limited number of time snapshots. The quasi-periodic motion of a deformable lung tumor caused by respiratory motion makes it suitable for treatment using DMD. The direct application of the DMD method to analyze the respiratory motion of the tumor is impractical because the tumor is three-dimensional and spans multiple CT slices. To predict the respiratory movement of lung tumors, a method called uniform angular interval (UAI) sampling was developed to generate snapshot vectors of equal length, which are suitable for DMD analysis. The effectiveness of this approach was confirmed by applying the UAI-DMD method to the 4D-CT data of ten patients with lung cancer. The results indicate that the UAI-DMD method effectively approximates the lung tumor's deformable boundary surface and nonlinear motion trajectories. The estimated tumor centroid is within 2 mm of the manually delineated centroid, a smaller margin of error compared to the traditional BSpline interpolation method, which has a margin of 3 mm. This methodology has the potential to be extended to reconstruct the 20-phase respiratory movement of a lung tumor based on dynamic features from 10-phase 4D-CT data, thereby enabling more accurate estimation of the planned target volume (PTV).

Surufatinib combined with photodynamic therapy induces ferroptosis to inhibit cholangiocarcinoma in vitro and in tumor models.

The curative effect of single therapy for advanced cholangiocarcinoma (CCA) is poor, thus investigating combined treatment strategies holds promise for improving prognosis. Surufatinib (SUR) is a novel multikinase inhibitor that has been confirmed to prolong survival of patients with advanced CCA. Photodynamic therapy (PDT) can also ablate advanced CCA and relieve biliary obstruction. In this study, we explored the anti-CCA effect of SUR combined with PDT, and explored the underlying mechanism. We found that SUR could effectively inhibit the abilities of proliferation, migration and metastasis in CCA cells (HUCCT-1, RBE). The ability of SUR to inhibit CCA was also confirmed by the HUCCT-1 cell xenograft model in Balb/c nude mice and CCA patient-derived organoids. SUR combined with PDT can significantly enhance the inhibitory effect on CCA, and can be alleviated by two ferroptosis inhibitors (Ferrostatin-1, Deferoxamine). By detecting the level of reactive oxygen species, lipid peroxides, malondialdehyde and glutathione, we further confirmed that SUR combined with PDT can inhibit CCA cells by inducing ferroptosis. Glutathione peroxidase 4 (GPX4) belongs to the glutathione peroxidase family and is mainly responsible for the metabolism of intracellular hydrogen peroxide. GPX4 inhibits ferroptosis by reducing cytotoxic lipid peroxides (L-OOH) to the corresponding alcohols (L-OH). Acyl-CoA synthetase long-chain family member 4 (ACSL4) is a member of the long-chain fatty acid coenzyme a synthetase family and is mainly involved in the biosynthesis and catabolism of fatty acids. ACSL4 induces ferroptosis by promoting the accumulation of lipid peroxides. Both SUR and PDT can induce ferroptosis by promoting ACSL4 and inhibiting GPX4. The regulation effect is found to be more significant in combined treatment group. In conclusion, SUR combined with PDT exerted an anti-CCA effect by inducing ferroptosis. Combination therapy provides a new idea for the clinical treatment of CCA.

Prediction Model and Risk Factor Analysis of Adjacent Segment Disease After L4-5 Transforaminal Lumbar Interbody Fusion Through Preoperative Radiographic Features.

STUDY DESIGN: A retrospective study. OBJECTIVE: To investigate the risk of adjacent segment disease (ASD) after L4-5 transforaminal lumbar interbody fusion (TLIF) in patients diagnosed with lumbar spinal stenosis (LSS), a prediction model for ASD is established and validated. METHODS: A retrospective study was carried out on a sample of 290 patients who underwent L4-5 TLIF at Zhongda Hospital, Southeast University, from January 2015 to January 2021. The study collected baseline data and preoperative radiographic features of L3-4 and L5-S1. The determination of the outcome variable was based on X-ray results spanning over 24 months and JOA scores. Multivariate logistic regression was used to identify the risk factors in constructing a nomogram. RESULTS: Independent risk factors for L3-4 degeneration after TLIF included osteoarthritis of L3-4 facet joints, L3-4 foraminal stenosis, L4 upper endplate osteochondritis, L3-4 local lordosis angle, and L3-4 spinal stenosis. Independent risk factors for L5-S1 degeneration after TLIF included osteoarthritis of L5-S1 facet joints, L5-S1 intervertebral disc degeneration, L5-S1 spinal stenosis, L5-S1 coronal imbalance, and S1 upper endplate osteochondritis. A predictive model was developed. The AUC for the prediction models at L3-4 and L5-S1 were .945 and .956. The calibration curve demonstrated good consistency between the predicted and actual probabilities. The DCA curve indicated the clinical benefit and practical value of this predictive model. CONCLUSION: This study established nomograms for postoperative degeneration at L3-4 and L5-S1 based on selected preoperative radiographic features. These models provide a valuable auxiliary decision-making system for clinicians and aid in early surgical decisions.

Changes of structural functional connectivity coupling and its correlations with cognitive function in patients with major depressive disorder.

BACKGROUND: Previous neuroimaging studies have reported structural and functional brain abnormalities in major depressive disorder (MDD). This study aimed to explore whether the coherence of structural-functional networks was affected by disease and investigate its correlation with clinical manifestations. METHODS: The severity of symptoms and cognitive function of 121 MDD patients and 139 healthy controls (HC) were assessed, and imaging data, including diffusion tensor imaging, T1 structural magnetic resonance imaging (MRI) and resting-state functional MRI, were collected. Spearman correlation coefficients of Kullback-Leibler similarity (KLS), fiber number (FN), fractional anisotropy (FA) and functional connectivity (FC) were calculated as coupling coefficients. Double-weight median correlation analysis was conducted to investigate the correlations between differences in brain networks and clinical assessments. RESULTS: The percentage of total correct response of delayed matching to sample and the percentage of delayed correct response of pattern recognition memory was lower in MDD. Compared with the HC, KLS-FC coupling between the parietal lobe and subcortical area, FA-FC coupling between the temporal and parietal lobe, and FN-FC coupling in the frontal lobe was lower in MDD. Several correlations between structural-functional connectivity and clinical manifestations were identified. LIMITATIONS: First, our study lacks longitudinal follow-up data. Second, the sample size was relatively small. Moreover, we only used the Anatomical Automatic Labeling template to construct the brain network. Finally, the validation of the causal relationship of neuroimaging-behavior factors was still insufficient. CONCLUSIONS: The alternation in structural-functional coupling were related to clinical characterization and might be involved in the neuropathology of depression.

Endoplasmic reticulum stress-mediated autophagy alleviates lipopolysaccharide-induced nucleus pulposus cell pyroptosis by inhibiting CHOP signaling in vitro.

Pyroptosis, a newly discovered pro-inflammatory programmed necrosis of cells, serves as an initiating and promoting event that leads to intervertebral disc (IVD) degeneration (IDD). Endoplasmic reticulum stress (ERS) and autophagy are vital regulatory mechanisms of cellular homeostasis, which is also closely related to IDD. However, the role and relationship of ERS and autophagy in the pyroptosis of nucleus pulposus cell (NPC) are not well understood. In this research, we aimed to elucidate the role and mechanism of ERS-C/EBP homologous protein (CHOP) in lipopolysaccharide (LPS)-induced cell pyroptosis and determine its interaction with autophagy. ERS and autophagy inducers or inhibitors were used or not in the preconditioning of rat NPCs. Cell viability, pyroptosis-related protein expression, caspase-1 activity assay, and enzyme-linked immunosorbent assay were performed to observe rat NPC pyroptosis after the treatment of LPS. Activation of the ERS pathway and autophagy were assessed by quantitative real-time PCR, western blot analyses, and immunofluorescence staining assay to classify the molecular mechanisms. Our results showed that LPS stimulation induced NPC pyroptosis with concomitant activation of the ERS-CHOP pathway and initiated autophagy. Activation of the ERS-CHOP pathway exacerbated rat NPC pyroptosis, whereas autophagy inhibited cell pyroptosis. LPS-induced cell pyroptosis and CHOP upregulation were negatively regulated by autophagy. LPS-induced autophagy was depressed by the ERS inhibitor but aggravated by the ERS inducer. Taken together, our findings suggested that LPS induced NPC pyroptosis by activating ERS-CHOP signaling and ERS mediated LPS-induced autophagy, which in turn alleviated NPC pyroptosis by inhibiting CHOP signaling.

Prognosis prediction and comparison between pancreatic signet ring cell carcinoma and pancreatic duct adenocarcinoma: a retrospective observational study.

Background: Pancreatic signet ring cell carcinoma (PSRCC) is a rare and aggressive cancer that has been reported primarily as case reports. Due to limited large-scale epidemiological and prognostic analyses, the outcomes of PSRCC patients varies greatly in the absence of recognized first-line treatment strategies. This study aimed to compare the clinical features, treatment, and prognosis of PSRCC and pancreatic ductal cell carcinoma (PDAC), the most common subtype of pancreatic cancer, and to establish predictive models for these subtypes. Methods: The data on PSRCC and PDAC patients from 1998 to 2018 was obtained from the Surveillance, Epidemiology, and End Results (SEER) database. Thereafter, the clinical, demographic, and treatment characteristics of the two groups and the differences and influencing factors of the two groups were evaluated by propensity score matching (PSM), Kaplan-Meier survival curves, Cox risk regression analyses, and least absolute shrinkage and selection operator (LASSO) analysis. Next, prognosis models were constructed and validated by KM and ROC analysis. Finally, a nomogram was constructed, based on the results of these analyses, to predict survival outcomes of PSRCC and PDAC patients. Results: A total of 84,789 patients (432 PSRCC and 84357 PDAC patients) were included in this study. The results of the study revealed that, compared to the PDAC patients, PSRCC patients were more likely to be male, aged between 58-72 years, have larger tumor masses, and less likely to undergo chemotherapy. Before PSM, the overall survival and cancer-specific survival of the PSRCC group were significantly lower than those PDAC group, but there was no difference in the prognosis of the two groups after PSM. Additionally, lymph node ratio (LNR), log odds of positive lymph node (LODDS), tumor size, age, T-stage, marital status, and summary stage were found to be independent prognostic factors for PSRCC. Lastly, the prediction model and nomogram based on these prognostic factors could accurately predict the survival rate of the patients in SEER datasets and external validation datasets. Conclusion: The prognosis of PSRCC and PDAC patients is similar under the same conditions; however, PSRCC patients may have more difficulty in receiving better treatment, thus resulting in their poor prognosis.

ATF4 renders human T-cell acute lymphoblastic leukemia cell resistance to FGFR1 inhibitors through amino acid metabolic reprogramming.

Abnormalities of FGFR1 have been reported in multiple malignancies, suggesting FGFR1 as a potential target for precision treatment, but drug resistance remains a formidable obstacle. In this study, we explored whether FGFR1 acted a therapeutic target in human T-cell acute lymphoblastic leukemia (T-ALL) and the molecular mechanisms underlying T-ALL cell resistance to FGFR1 inhibitors. We showed that FGFR1 was significantly upregulated in human T-ALL and inversely correlated with the prognosis of patients. Knockdown of FGFR1 suppressed T-ALL growth and progression both in vitro and in vivo. However, the T-ALL cells were resistant to FGFR1 inhibitors AZD4547 and PD-166866 even though FGFR1 signaling was specifically inhibited in the early stage. Mechanistically, we found that FGFR1 inhibitors markedly increased the expression of ATF4, which was a major initiator for T-ALL resistance to FGFR1 inhibitors. We further revealed that FGFR1 inhibitors induced expression of ATF4 through enhancing chromatin accessibility combined with translational activation via the GCN2-eIF2α pathway. Subsequently, ATF4 remodeled the amino acid metabolism by stimulating the expression of multiple metabolic genes ASNS, ASS1, PHGDH and SLC1A5, maintaining the activation of mTORC1, which contributed to the drug resistance in T-ALL cells. Targeting FGFR1 and mTOR exhibited synergistically anti-leukemic efficacy. These results reveal that FGFR1 is a potential therapeutic target in human T-ALL, and ATF4-mediated amino acid metabolic reprogramming contributes to the FGFR1 inhibitor resistance. Synergistically inhibiting FGFR1 and mTOR can overcome this obstacle in T-ALL therapy.

Intersection of nanomaterials and organoids technology in biomedicine.

Organoids are stem cell-derived, self-organizing, 3D structures. Compared to the conventional 2D cell culture method, 3D cultured organoids contain a variety of cell types that can form functional "micro-organs" and can be used to simulate the occurrence process and physiological pathological state of organ tissues more effectively. Nanomaterials (NMs) are becoming indispensable in the development of novel organoids. Understanding the application of nanomaterials in organoid construction can, therefore, provide researchers with ideas for the development of novel organoids. Here, we discuss the application status of NMs in various organoid culture systems and the research direction of NMs combined with organoids in the biomedical field.

Identification of immune related gene signature for predicting prognosis of cholangiocarcinoma patients.

Objective: To identify the gene subtypes related to immune cells of cholangiocarcinoma and construct an immune score model to predict the immunotherapy efficacy and prognosis for cholangiocarcinoma. Methods: Based on principal component analysis (PCA) algorithm, The Cancer Genome Atlas (TCGA)-cholangiocarcinoma, GSE107943 and E-MTAB-6389 datasets were combined as Joint data. Immune genes were downloaded from ImmPort. Univariate Cox survival analysis filtered prognostically associated immune genes, which would identify immune-related subtypes of cholangiocarcinoma. Least absolute shrinkage and selection operator (LASSO) further screened immune genes with prognosis values, and tumor immune score was calculated for patients with cholangiocarcinoma after the combination of the three datasets. Kaplan-Meier curve analysis determined the optimal cut-off value, which was applied for dividing cholangiocarcinoma patients into low and high immune score group. To explore the differences in tumor microenvironment and immunotherapy between immune cell-related subtypes and immune score groups of cholangiocarcinoma. Results: 34 prognostic immune genes and three immunocell-related subtypes with statistically significant prognosis (IC1, IC2 and IC3) were identified. Among them, IC1 and IC3 showed higher immune cell infiltration, and IC3 may be more suitable for immunotherapy and chemotherapy. 10 immune genes with prognostic significance were screened by LASSO regression analysis, and a tumor immune score model was constructed. Kaplan-Meier (KM) and receiver operating characteristic (ROC) analysis showed that RiskScore had excellent prognostic prediction ability. Immunohistochemical analysis showed that 6 gene (NLRX1, AKT1, CSRP1, LEP, MUC4 and SEMA4B) of 10 genes were abnormal expressions between cancer and paracancer tissue. Immune cells infiltration in high immune score group was generally increased, and it was more suitable for chemotherapy. In GSE112366-Crohn's disease dataset, 6 of 10 immune genes had expression differences between Crohn's disease and healthy control. The area under ROC obtained 0.671 based on 10-immune gene signature. Moreover, the model had a sound performance in Crohn's disease. Conclusion: The prediction of tumor immune score model in predicting immune microenvironment, immunotherapy and chemotherapy in patients with cholangiocarcinoma has shown its potential for indicating the effect of immunotherapy on patients with cholangiocarcinoma.

Prognosis comparison between small cell carcinoma of ovary and high-grade serous ovarian cancer: A retrospective observational cohort study.

Background: Small cell carcinoma of ovary (SCCO) is a rare and aggressive cancer primarily reported in the form of case reports. Due to limited epidemiological and prognostic analyses based on large populations, SCCO has varied considerably without prognostic models and a recognized first-line treatment strategy. The study aimed to compare the clinical characteristics, treatment methods, and prognosis of SCCO and high-grade serous ovarian cancer (HGSOC), the most prevalent subtype of ovarian cancer, in a large sample and develop a predictive model for these two subtypes. Methods: Data from the Surveillance, Epidemiology, and End Results program were analyzed for patients with SCCO or HGSOC from 2000 to 2017. Clinical, demographic, and treatment characteristics were compared between the two groups. Propensity-score matching, Cox risk regression analysis, and Kaplan-Meier survival curves were used to assess the data. Finally, a nomogram was developed to predict the patient survival time. Results: A total of 32,185 women, including 31,979 (99.4%) diagnosed with HGSOC and 206 (0.6%) diagnosed with SCCO, were identified. Age ≤ 51 years, single, median house income less than $70,000, early stage, and unilateral disease were more common characteristics of patients with SCCO than those with HGSOC. Patients with SCCO were more likely to receive radiotherapy (6.8% vs. 0.8%, p <0.001) and have tumors ≥ 141 mm (38.3% vs. 9.7%, p <0.001) than patients with HGSOC. The independent risk factors for SCCO patients included older age at diagnosis, advanced stage, surgery, radiotherapy, chemotherapy, larger tumor size, and bilateral tumor. Overall and cancer-specific survival rates were significantly lower for SCCO than more malignant HGSOC. Prognostic models and nomograms had been constructed to predict the individual survival rates of patients with SCCO and HGSOC. Conclusion: Patients with SCCO presented with the early-stage disease more frequently than patients with HGSOC and had decreased overall and cancer-specific survival rates.

Low-Depth Hamiltonian Simulation by an Adaptive Product Formula.

Various Hamiltonian simulation algorithms have been proposed to efficiently study the dynamics of quantum systems on a quantum computer. The existing algorithms generally approximate the time evolution operators, which may need a deep quantum circuit that is beyond the capability of near-term noisy quantum devices. Here, focusing on the time evolution of a fixed input quantum state, we propose an adaptive approach to construct a low-depth time evolution circuit. By introducing a measurable quantifier that characterizes the simulation error, we use an adaptive strategy to learn the shallow quantum circuit that minimizes that error. We numerically test the adaptive method with electronic Hamiltonians of the H_{2}O and H_{4} molecules, and the transverse field Ising model with random coefficients. Compared to the first-order Suzuki-Trotter product formula, our method can significantly reduce the circuit depth (specifically the number of two-qubit gates) by around two orders while maintaining the simulation accuracy. We show applications of the method in simulating many-body dynamics and solving energy spectra with the quantum Krylov algorithm. Our work sheds light on practical Hamiltonian simulation with noisy-intermediate-scale-quantum devices.

A pH-responsive metal-organic framework for the co-delivery of HIF-2α siRNA and curcumin for enhanced therapy of osteoarthritis.

The occurrence of osteoarthritis (OA) is highly correlated with the reduction of joint lubrication performance, in which persistent excessive inflammation and irreversible destruction of cartilage dominate the mechanism. The inadequate response to monotherapy methods, suboptimal efficacy caused by undesirable bioavailability, short retention, and lack of stimulus-responsiveness, are few unresolved issues. Herein, we report a pH-responsive metal-organic framework (MOF), namely, MIL-101-NH2, for the co-delivery of anti-inflammatory drug curcumin (CCM) and small interfering RNA (siRNA) for hypoxia inducible factor (HIF-2α). CCM and siRNA were loaded via encapsulation and surface coordination ability of MIL-101-NH2. Our vitro tests showed that MIL-101-NH2 protected siRNA from nuclease degradation by lysosomal escape. The pH-responsive MIL-101-NH2 gradually collapsed in an acidic OA microenvironment to release the CCM payloads to down-regulate the level of pro-inflammatory cytokines, and to release the siRNA payloads to cleave the target HIF-2α mRNA for gene-silencing therapy, ultimately exhibiting the synergetic therapeutic efficacy by silencing HIF-2α genes accompanied by inhibiting the inflammation response and cartilage degeneration of OA. The hybrid material reported herein exhibited promising potential performance for OA therapy as supported by both in vitro and in vivo studies and may offer an efficacious therapeutic strategy for OA utilizing MOFs as host materials.

Remodeling the Tumor Microenvironment with Core-Shell Nanosensitizer Featuring Dual-Modal Imaging and Multimodal Therapy for Breast Cancer.

To improve the efficiency of radiation therapy (RT) for breast cancer, a designable multifunctional core-shell nanocomposite of FeP@Pt is constructed using Fe(III)-polydopamine (denoted as FeP) as the core and platinum particles (Pt) as the shell. The hybrid structure is further covered with hyaluronic acid (HA) to give the final nanoplatform of FeP@Pt@HA (denoted as FPH). FPH exhibits good biological stability, prolongs blood circulation time, and is simultaneously endowed with tumor-targeting ability. With CD44-mediated endocytosis of HA, FPH can be internalized by cancer cells and activated by the tumor microenvironment (TME). The redox reaction between Fe3+ in FPH and endogenous glutathione (GSH) or/and hydrogen peroxide (H2O2) initiates ferroptosis therapy by promoting GSH exhaustion and •OH generation. Moreover, FPH has excellent photothermal conversion efficiency and can absorb near-infrared laser energy to promote the above catalytic reaction as well as to achieve photothermal therapy (PTT). Ferroptosis therapy and PTT are further accompanied by the catalase activity of Pt nanoshells to accelerate O2 production and the high X-ray attenuation coefficient of Pt for enhanced radiotherapy (RT). Apart from the therapeutic modalities, FPH exhibits dual-modal contrast enhancement in infrared (IR) thermal imaging and computed tomography (CT) imaging, offering potential in imaging-guided cancer therapy. In this article, the nanoplatform can remodel the TME through the production of O2, GSH- and H2O2-depletion, coenhanced PTT, ferroptosis, and RT. This multimodal nanoplatform is anticipated to shed light on the design of TME-activatable materials to enhance the synergism of treatment results and enable the establishment of efficient nanomedicine.

Comprehensive Analysis of the Potential Immune-Related Biomarker ATG101 that Regulates Apoptosis of Cholangiocarcinoma Cells After Photodynamic Therapy.

Autophagy related gene 101 (ATG101) plays a significant role in the occurrence and development of tumours by responding to stress. Our research aims to illustrate the correlation between the expression of ATG101 and tumor prognosis and its potential role and mechanism in tumor immunity and photodynamic therapy (PDT). First, integrated analysis of The Cancer Genome Atlas and Genotype-Tissue Expression portals were used to analyse the expression of ATG101. Then, Kaplan-Meier curves was applied in cholangiocarcinoma (CHOL) and liver hepatocellular carcinoma (LIHC) datasets for survival analysis. Next, the relationship between ATG101 expression and six immune cells, the immune microenvironment and immune checkpoints was analysed. Besides, the relationship between the expression of ATG101 and methyltransferase. GSEA was used to study the function and the related transcript factors of ATG101 in CHOL and LIHC. The effect of PDT on ATG101 was verified by microarray, qPCR and western blot. Then the effect of ATG101 and its regulatory factors on apoptosis were verified by siRNA, lentivirus transfection and Chip-qPCR. Comprehensive analysis showed that ATG101 was overexpressed in different tumours. Kaplan-Meier curves found that ATG101 was associated with poor prognosis in tumours (including CHOL and LIHC). We found that ATG101 can be used as a target and prognostic marker of tumour immunotherapy for different tumours. We also found that ATG101 regulates DNA methylation. GSEA analysis showed that ATG101 may play a critical role in CHOL and LIHC. Subsequent validation tests confirmed that the up-regulated ATG101 after PDT treatment is not conducive to the occurrence of apoptosis of cholangiocarcinoma cells. The high expression of ATG101 may be induced by the early stress gene EGR2. Our study highlights the significance of ATG101 in the study of tumour immunity and photodynamic therapy from a pan-cancer perspective.

The influence of non-conformal grid interfaces on the results of large eddy simulation of centrifugal blood pumps.

BACKGROUND: Computational fluid dynamics has been widely used to assist the design and evaluation of blood pumps. Discretization errors associated with computational grid may influence the credibility of numerical simulations. Non-conformal grid interfaces commonly exist in rotary machines, including rotary blood pumps. Should grid size across the interface differ greatly, large errors may occur. METHODS: This study explored the effects of non-conformal grid interface on the prediction of the flow field and hemolysis in blood pumps using large eddy simulation (LES). Two benchmarks, a nozzle model and a centrifugal blood pump were chosen as test cases. RESULTS: This study found that non-conformal grid interfaces with considerable change of grid sizes led to discontinuities of flow variables and brought errors to metrics such as pressure head (7%) and hemolysis (up to 14%). CONCLUSIONS: The results on the full unstructured grid are more accurate with negligible changes of flow variables across the non-conformal grid interface. A full unstructured grid should be employed for centrifugal blood pumps to minimize the influence of non-conformal grid interfaces for LES simulations.

Comprehensive Analysis of the Tumor Microenvironment and Ferroptosis-Related Genes Predict Prognosis with Ovarian Cancer.

The early diagnosis of ovarian cancer (OC) is critical to improve the prognosis and prevent recurrence of patients. Nevertheless, there is still a lack of factors which can accurately predict it. In this study, we focused on the interaction of immune infiltration and ferroptosis and selected the ESTIMATE algorithm and 15 ferroptosis-related genes (FRGs) to construct a novel E-FRG scoring model for predicting overall survival of OC patients. The gene expression and corresponding clinical characteristics were obtained from the TCGA dataset (n = 375), GSE18520 (n = 53), and GSE32062 (n = 260). A total of 15 FRGs derived from FerrDb with the immune score and stromal score were identified in the prognostic model by using least absolute shrinkage and selection operator (LASSO)-penalized COX regression analysis. The Kaplan-Meier survival analysis and time-dependent ROC curves performed a powerful prognostic ability of the E-FRG model via multi-validation. Gene Set Enrichment Analysis and Gene Set Variation Analysis elucidate multiple potential pathways between the high and low E-FRG score group. Finally, the proteins of different genes in the model were verified in drug-resistant and non-drug-resistant tumor tissues. The results of this research provide new prospects in the role of immune infiltration and ferroptosis as a helpful tool to predict the outcome of OC patients.

Novel perspective in pancreatic cancer therapy: Targeting ferroptosis pathway.

Pancreatic cancer is a highly lethal malignancy with low resection and survival rates and is not sensitive to radiotherapy and chemotherapy. Ferroptosis is a novel form of nonapoptotic regulated cell death characterized by the accumulation of lipid peroxides and reactive oxygen species involved in iron metabolism. Ferroptosis has a significant role in the occurrence and development of various tumors. Previous studies have shown that regulating ferroptosis-induced cell death inhibited tumor growth in pancreatic cancer and was synergistic with other antitumor drugs to improve treatment sensitivity. Herein, we discuss the mechanism, inducers, and developments of ferroptosis in pancreatic cancer to provide new strategies for the treatment of the malignancy.

A Novel Ferroptosis-Related 4-Gene Prognostic Signature for Cholangiocarcinoma and Photodynamic Therapy.

Cholangiocarcinoma is the second most common malignant tumor in the hepatobiliary system. Compared with data on hepatocellular carcinoma, fewer public data and prognostic-related studies on cholangiocarcinoma are available, and effective prognostic prediction methods for cholangiocarcinoma are lacking. In recent years, ferroptosis has become an important subject of tumor research. Some studies have indicated that ferroptosis plays an important role in hepatobiliary cancers. However, the prediction of the prognostic effect of ferroptosis in patients with cholangiocarcinoma has not been reported. In addition, many reports have described the ability of photodynamic therapy (PDT), a potential therapy for cholangiocarcinoma, to regulate ferroptosis by generating reactive oxygen species (ROS). By constructing ferroptosis scores, the prognoses of patients with cholangiocarcinoma can be effectively predicted, and potential gene targets can be discovered to further enhance the efficacy of PDT. In this study, gene expression profiles and clinical information (TCGA, E-MTAB-6389, and GSE107943) of patients with cholangiocarcinoma were collected and divided into training sets and validation sets. Then, a model of the ferroptosis gene signature was constructed using least absolute shrinkage and selection operator (LASSO)-penalized Cox regression analysis. Furthermore, through the analysis of RNA-seq data after PDT treatment of cholangiocarcinoma, PDT-sensitive genes were obtained and verified by immunohistochemistry staining and Western blot. The results of this study provide new insight for predicting the prognosis of cholangiocarcinoma and screening target genes that enhance the efficacy of PDT.

Sulfasalazine Sensitizes Polyhematoporphyrin-Mediated Photodynamic Therapy in Cholangiocarcinoma by Targeting xCT.

Cholangiocarcinoma (CCA), which is highly malignant, shows a relatively poor prognosis, due to the insensitivity of the tumour to chemotherapy and radiotherapy. Photodynamic therapy (PDT) has become a promising palliative therapeutic option for patients with unresectable cholangiocarcinoma (CCA), while the functional amount of ROS is limited by intracellular redox systemen. Sulfasalazine (SASP), a well-known anti-inflammatory agent, which also acts as an inhibitor of the amino acid transport system xc (xCT), decreases the intracellular glutathione (GSH) level, thus weakening the antioxidant defence of the cell by inhibition of the antiporter. However, the combination of SASP and PDT remains unexplored. We have reported that polyhematoporphyrin (PHP)-mediated PDT inhibits the cell viability of CCA cells and organoids. Furthermore, in PHP-enriched HCCC-9810 and TFK-1CCA cells, SASP enhances the sensitivity to PHP-mediated PDT through a GSH-dependent mechanism. We found that PHP-PDT can up-regulate xCT expression to promote cells against overloaded ROS, while SASP reduces GSH levels. After the combination of SASP and PHP-PDT, cell viability and GSH levels were significantly inhibited. xCT was also observed to be inhibited by SASP in human organoid samples. Our findings suggest that, in combination with PDT, SASP has potential as a promising approach against CCA.