Predictive value of triglyceride glucose index combined with neutrophil-to-lymphocyte ratio for major adverse cardiac events after PCI for acute ST-segment elevation myocardial infarction.

Acute ST-segment elevation myocardial infarction (STEMI) is a severe cardiovascular disease that poses a significant threat to the life and health of patients. This study aimed to investigate the predictive value of triglyceride glucose index (TyG) combined with neutrophil-to-lymphocyte ratio (NLR) for in-hospital cardiac adverse event (MACE) after PCI in STEMI patients. From October 2019 to June 2023, 398 STEMI patients underwent emergency PCI in the Second People's Hospital of Hefei. Stepwise regression backward method and multivariate logistic regression analysis were used to screen the independent risk factors of MACE in STEMI patients. To construct the prediction model of in-hospital MACE after PCI in STEMI patients: Grace score model is the old model (model A); TyG combined with NLR model (model B); Grace score combined with TyG and NLR model is the new model (model C). We assessed the clinical usefulness of the predictive model by comparing Integrated Discrimination Improvement (IDI), Net Reclassification Index (NRI), Receiver Operating Characteristic Curve (ROC), and Decision Curve Analysis (DCA). Stepwise regression and multivariate logistic regression analysis showed that TyG and NLR were independent risk factors for in-hospital MACE after PCI in STEMI patients. The constructed Model C was compared to Model A. Results showed NRI 0.5973; NRI + 0.3036, NRI - 0.2937, IDI 0.3583. These results show that the newly developed model C predicts the results better than model A, indicating that the model is more accurate. The ROC analysis results showed that the AUC of Model A for predicting MACE in STEMI was 0.749. Model B predicted MACE in STEMI with an AUC of 0.685. Model C predicted MACE in STEMI with an AUC of 0.839. For DCA, Model C has a better net return between threshold probability 0.1 and 0.78, which is better than Model A and Model B. In this study, by combining TyG, NLR, and Grace score, it was shown that TyG combined with NLR could reasonably predict the occurrence of MACE after PCI in STEMI patients and the clinical utility of the prediction model.

Mitochondrial RNA modification-based signature to predict prognosis of lower grade glioma: a multi-omics exploration and verification study.

Mitochondrial RNA modification (MRM) plays a crucial role in regulating the expression of key mitochondrial genes and promoting tumor metastasis. Despite its significance, comprehensive studies on MRM in lower grade gliomas (LGGs) remain unknown. Single-cell RNA-seq data (GSE89567) was used to evaluate the distribution functional status, and correlation of MRM-related genes in different cell types of LGG microenvironment. We developed an MRM scoring system by selecting potential MRM-related genes using LASSO regression analysis and the Random Survival Forest algorithm, based on multiple bulk RNA-seq datasets from TCGA, CGGA, GSE16011, and E-MTAB-3892. Analysis was performed on prognostic and immunological features, signaling pathways, metabolism, somatic mutations and copy number variations (CNVs), treatment responses, and forecasting of potential small-molecule agents. A total of 35 MRM-related genes were selected from the literature. Differential expression analysis of 1120 normal brain tissues and 529 LGGs revealed that 22 and 10 genes were upregulated and downregulated, respectively. Most genes were associated with prognosis of LGG. METLL8, METLL2A, TRMT112, and METTL2B were extensively expressed in all cell types and different cell cycle of each cell type. Almost all cell types had clusters related to mitochondrial RNA processing, ribosome biogenesis, or oxidative phosphorylation. Cell-cell communication and Pearson correlation analyses indicated that MRM may promoting the development of microenvironment beneficial to malignant progression via modulating NCMA signaling pathway and ICP expression. A total of 11 and 9 MRM-related genes were observed by LASSO and the RSF algorithm, respectively, and finally 6 MRM-related genes were used to establish MRM scoring system (TRMT2B, TRMT11, METTL6, METTL8, TRMT6, and TRUB2). The six MRM-related genes were then validated by qPCR in glioma and normal tissues. MRM score can predict the malignant clinical characteristics, abundance of immune infiltration, gene variation, clinical outcome, the enrichment of signaling pathways and metabolism. In vitro experiments demonstrated that silencing METTL8 significantly curbs glioma cell proliferation and enhances apoptosis. Patients with a high MRM score showed a better response to immunotherapies and small-molecule agents such as arachidonyl trifluoromethyl ketone, MS.275, AH.6809, tacrolimus, and TTNPB. These novel insights into the biological impacts of MRM within the glioma microenvironment underscore its potential as a target for developing precise therapies, including immunotherapeutic approaches.

Healthy tissue metabolism assessed by [18F]FDG PET/CT as a marker of prognosis and adverse events in advanced Hodgkin lymphoma patients.

The aim of the study was to assess healthy tissue metabolism (HTM) using 2-deoxy-2-[18F]fluoro-D-glucose ([18F]FDG) positron emission tomography/computed tomography (PET/CT) during chemotherapy in Hodgkin lymphoma (HL) and the association of HTM with baseline metabolic tumour volume (MTV), haematological parameters, adverse events (AEs), early response and progression-free survival (PFS). We retrospectively identified 200 patients with advanced HL from the RATHL trial with [18F]FDG-PET/CT before (PET0) and following 2 cycles of chemotherapy (PET2). [18F]FDG-uptake was measured in bone marrow (BM), spleen, liver and mediastinal blood pool (MBP). Deauville score (DS) 1-3 was used to classify responders and DS 4-5, non-responders. [18F]FDG-uptake decreased significantly in BM and spleen and increased in liver and MBP at PET2 (all p < 0.0001), but was not associated with MTV. Higher BM uptake at PET0 was associated with lower baseline haemoglobin and higher absolute neutrophil counts, platelets, and white blood cells. High BM, spleen, and liver uptake at PET0 was associated with neutropenia after cycles 1-2. BM uptake at PET0 was associated with treatment failure at PET2 and non-responders with higher BM uptake at PET2 had significantly inferior PFS (p = 0.023; hazard ratio = 2.31). Based on these results, we concluded that the change in HTM during chemotherapy was most likely a direct impact of chemotherapy rather than a change in MTV. BM uptake has prognostic value in HL.

Her-2/neu gene amplification and its correlation with other prognostic factors in Iranian breast cancer patients.

BACKGROUND: Breast cancer is one of the most common diseases in females, arising from overexpression of a variety of oncogenes like HER2/neu. The amplification rate of this gene is variable in different breast cancer patients. In this study, the amplification of the HER2/neu oncogene was distinguished in breast cancer patients and its correlation with prognostic factors. Also, the simultaneous effect of prognostic factors on the occurrence of a specific prognostic factor was investigated. MATERIALS AND METHODS: The multiplex PCR technique was used to assay the amplification of the HER2/neu oncogene in breast cancer patients. After extracting DNA from 100 tumor tissue and 8 normal breast tissue samples, the amplification of the HER2/neu gene was distinguished by the co-amplification of a single-copy reference gene, γ-IFN, and the target gene HER2/neu in the PCR reaction and using the Gel analyzer software. SPSS 23 and STATA 9.1 software were used for statistical analysis. RESULTS: The HER2/neu gene was amplification in 30% of the tumor samples. The statistical analysis showed a statistically significant relationship between HER2/neu gene amplification and progesterone receptors. Amplification of the HER2/neu gene significantly increases the chance of lymph node involvement. Also, the amplification of this gene in tumors with histological grade II tissue is more than grade I. CONCLUSION: The amplification of the HER2/neu gene can be used as an independent prognostic factor in predicting lymph node involvement and histological grade in breast cancer patients.

Prognostic significance of CHCHD2P9 and ZNF204P in breast cancer: exploring their expression patterns and associations with malignancy-related genes.

BACKGROUND: Non-coding RNAs (ncRNAs) have a crucial impact on diverse cellular processes, influencing the progression of breast cancer (BC). The objective of this study was to identify novel ncRNAs in BC with potential effects on patient survival and disease progression. METHODS: We utilized the cancer genome atlas data to identify ncRNAs associated with BC pathogenesis. We explored the association between these ncRNA expressions and survival rates. A risk model was developed using candidate ncRNA expression and beta coefficients obtained from a multivariate Cox regression analysis. Co-expression networks were constructed to determine potential relationships between these ncRNAs and molecular pathways. For validation, we employed BC samples and the RT-qPCR method. RESULTS: Our findings revealed a noteworthy increase in the expression of AC093850.2 and CHCHD2P9 in BC, which was correlated with a poor prognosis. In contrast, ADAMTS9-AS1 and ZNF204P displayed significant downregulation and were associated with a favorable prognosis. The risk model, incorporating these four ncRNAs, robustly predicted patient survival. The co-expression network showed an effective association between levels of AC093850.2, CHCHD2P9, ADAMTS9-AS1, and ZNF204P and genes involved in pathways like metastasis, angiogenesis, metabolism, and DNA repair. The RT-qPCR results verified notable alterations in the expression of CHCHD2P9 and ZNF204P in BC samples. Pan-cancer analyses revealed alterations in the expression of these two ncRNAs across various cancer types. CONCLUSION: This study presents a groundbreaking discovery, highlighting the substantial dysregulation of CHCHD2P9 and ZNF204P in BC and other cancers, with implications for patient survival.

Delayed epistaxis after endoscopic transnasal pituitary tumor resection: clinical characteristics, risk factors, treatment and prevention.

BACKGROUND: Delayed epistaxis after endoscopic transnasal pituitary tumor resection (ETPTR) is a critical complication, tending to cause aspiration or hemorrhagic shock. This study assessed clinical characteristics, risk factors, and provide treatment and prevention advice of this complication. METHODS: This was a retrospective monocentric analysis of 862 patients who underwent ETPTR. Statistical analyses of clinical data revealed the incidence, sources and onset time of delayed epistaxis. Univariate analysis and binary logistic regression were used to identify risk factors. RESULTS: The incidence of delayed epistaxis was 2.78% (24/862), with an average onset time of 20.71 ± 7.39 days. The bleeding sources were: posterior nasal septal artery branch of sphenopalatine artery (12/24), multiple inflammatory mucosae (8/24), sphenopalatine artery trunk (3/24) and sphenoid sinus bone (1/24). Univariate analysis and binary logistic regression analysis confirmed that hypertension, nasal septum deviation, chronic rhinosinusitis and growth hormone pituitary tumor subtype were independent risk factors for delayed epistaxis. Sex, age, history of diabetes, tumor size, tumor invasion and operation time were not associated with delayed epistaxis. All patients with delayed epistaxis were successfully managed through endoscopic transnasal hemostasis without recurrence. CONCLUSIONS: Delayed epistaxis after ETPTR tends to have specific onset periods and risk factors. Prevention of these characteristics may reduce the occurrence of delayed epistaxis. Endoscopic transnasal hemostasis is recommended as the preferred treatment for delayed epistaxis.

N6-methyladenosine-modified SENP1, identified by IGF2BP3, is a novel molecular marker in acute myeloid leukemia and aggravates progression by activating AKT signal via de-SUMOylating HDAC2.

BACKGROUND: Elevated evidence suggests that the SENPs family plays an important role in tumor progression. However, the role of SENPs in AML remains unclear. METHODS: We evaluated the expression pattern of SENP1 based on RNA sequencing data obtained from OHSU, TCGA, TARGET, and MILE datasets. Clinical samples were used to verify the expression of SENP1 in the AML cells. Lentiviral vectors shRNA and sgRNA were used to intervene in SENP1 expression in AML cells, and the effects of SENP1 on AML proliferation and anti-apoptosis were detected using in vitro and in vivo models. Chip-qPCR, MERIP-qPCR, CO-IP, RNA pulldown, and dual-luciferase reporter gene assays were used to explore the regulatory mechanisms of SNEP1 in AML. RESULTS: SENP1 was significantly upregulated in high-risk AML patients and closely related to poor prognosis. The AKT/mTOR signaling pathway is a key downstream pathway that mediates SENP1's regulation of AML proliferation and anti-apoptosis. Mechanistically, the CO-IP assay revealed binding between SENP1 and HDAC2. SUMO and Chip-qPCR assays suggested that SENP1 can desumoylate HDAC2, which enhances EGFR transcription and activates the AKT pathway. In addition, we found that IGF2BP3 expression was upregulated in high-risk AML patients and was positively correlated with SENP1 expression. MERIP-qPCR and RIP-qPCR showed that IGF2BP3 binds SENP1 3-UTR in an m6A manner, enhances SENP1 expression, and promotes AKT pathway conduction. CONCLUSIONS: Our findings reveal a distinct mechanism of SENP1-mediated HDAC2-AKT activation and establish the critical role of the IGF2BP3/SENP1signaling axis in AML development.

Triglyceride-glucose index is associated with myocardial ischemia and poor prognosis in patients with ischemia and no obstructive coronary artery disease.

BACKGROUND: Ischemia and no obstructive coronary artery disease (INOCA) is increasingly recognized and associated with poor outcomes. The triglyceride-glucose (TyG) index is a reliable alternative measure of insulin resistance significantly linked to cardiovascular disease and adverse prognosis. We investigated the association between the TyG index and myocardial ischemia and the prognosis in INOCA patients. METHODS: INOCA patients who underwent both coronary angiography and myocardial perfusion imaging (MPI) were included consecutively. All participants were divided into three groups according to TyG tertiles (T1, T2, and T3). Abnormal MPI for myocardial ischemia in individual coronary territories was defined as summed stress score (SSS) ≥ 4 and summed difference score (SDS) ≥ 2. SSS refers to the sum of all defects in the stress images, and SDS is the difference of the sum of all defects between the rest images and stress images. All patients were followed up for major adverse cardiac events (MACE). RESULTS: Among 332 INOCA patients, 113 (34.0%) had abnormal MPI. Patients with higher TyG index had a higher rate of abnormal MPI (25.5% vs. 32.4% vs. 44.1%; p = 0.012). Multivariate logistic analysis showed that a high TyG index was significantly correlated with abnormal MPI in INOCA patients (OR, 1.901; 95% CI, 1.045-3.458; P = 0.035). During the median 35 months of follow-up, 83 (25%) MACE were recorded, and a higher incidence of MACE was observed in the T3 group (T3 vs. T2 vs. T1: 36.9% vs. 21.6% vs. 16.4%, respectively; p = 0.001). In multivariate Cox regression analysis, the T3 group was significantly associated with the risk of MACE compared to the T1 group (HR, 2.338; 95% CI 1.253-4.364, P = 0.008). CONCLUSION: This study indicates for the first time that the TyG index is significantly associated with myocardial ischemia and poor prognosis among INOCA patients.

Development and validation of a prognostic model for assessing long COVID risk following Omicron wave-a large population-based cohort study.

BACKGROUND: Long coronavirus disease (COVID) after COVID-19 infection is continuously threatening the health of people all over the world. Early prediction of the risk of Long COVID in hospitalized patients will help clinical management of COVID-19, but there is still no reliable and effective prediction model. METHODS: A total of 1905 hospitalized patients with COVID-19 infection were included in this study, and their Long COVID status was followed up 4-8 weeks after discharge. Univariable and multivariable logistic regression analysis were used to determine the risk factors for Long COVID. Patients were randomly divided into a training cohort (70%) and a validation cohort (30%), and factors for constructing the model were screened using Lasso regression in the training cohort. Visualize the Long COVID risk prediction model using nomogram. Evaluate the performance of the model in the training and validation cohort using the area under the curve (AUC), calibration curve, and decision curve analysis (DCA). RESULTS: A total of 657 patients (34.5%) reported that they had symptoms of long COVID. The most common symptoms were fatigue or muscle weakness (16.8%), followed by sleep difficulties (11.1%) and cough (9.5%). The risk prediction nomogram of age, diabetes, chronic kidney disease, vaccination status, procalcitonin, leukocytes, lymphocytes, interleukin-6 and D-dimer were included for early identification of high-risk patients with Long COVID. AUCs of the model in the training cohort and validation cohort are 0.762 and 0.713, respectively, demonstrating relatively high discrimination of the model. The calibration curve further substantiated the proximity of the nomogram's predicted outcomes to the ideal curve, the consistency between the predicted outcomes and the actual outcomes, and the potential benefits for all patients as indicated by DCA. This observation was further validated in the validation cohort. CONCLUSIONS: We established a nomogram model to predict the long COVID risk of hospitalized patients with COVID-19, and proved its relatively good predictive performance. This model is helpful for the clinical management of long COVID.

Stemness related lncRNAs signature for the prognosis and tumor immune microenvironment of ccRCC patients.

Long non-coding RNAs (lncRNAs) and cancer stem cells (CSCs) are crucial for the growth, migration, recurrence, and medication resistance of tumors. However, the impact of lncRNAs related to stemness on the outcome and tumor immune microenvironment (TIME) in clear cell renal cell carcinoma (ccRCC) is still unclear. In this study, we aimed to predict the outcome and TIME of ccRCC by constructing a stem related lncRNAs (SRlncRNAs) signature. We firstly downloaded ccRCC patients' clinical data and RNA sequencing data from UCSC and TCGA databases, and abtained the differentially expressed lncRNAs highly correlated with stem index in ccRCC through gene expression differential analysis and Pearson correlation analysis. Then, we selected suitable SRlncRNAs for constructing a prognostic signature of ccRCC patients by LASSO Cox regression. Further, we used nomogram and Kaplan Meier curves to evaluate the SRlncRNA signature for the prognose in ccRCC. At last, we used ssGSEA and GSVA to evaluate the correlation between the SRlncRNAs signature and TIME in ccRCC. Finally, We obtained a signtaure based on six SRlncRNAs, which are correlated with TIME and can effectively predict the ccRCC patients' prognosis. The SRlncRNAs signature may be a noval prognostic indicator in ccRCC.

Soluble immune checkpoints: implications for cancer prognosis and response to immune checkpoint therapy and conventional therapies.

Longitudinal sampling of tumor tissue from patients with solid cancers, aside from melanoma and a few other cases, is often unfeasible, and thus may not capture the plasticity of interactions between the tumor and immune system under selective pressure of a given therapy. Peripheral blood analyses provide salient information about the human peripheral immunome while offering technical and practical advantages over traditional tumor biopsies, and should be utilized where possible alongside interrogation of the tumor. Some common blood-based biomarkers used to study the immune response include immune cell subsets, circulating tumor DNA, and protein analytes such as cytokines. With the recent explosion of immune checkpoint inhibitors (ICI) as a modality of treatment in multiple cancer types, soluble immune checkpoints have become a relevant area of investigation for peripheral immune-based biomarkers. However, the exact functions of soluble immune checkpoints and their roles in cancer for the most part remain unclear. This review discusses current literature on the production, function, and expression of nine soluble immune checkpoints - sPD-L1, sPD-1, sCTLA4, sCD80, sTIM3, sLAG3, sB7-H3, sBTLA, and sHVEM - in patients with solid tumors, and explores their role as biomarkers of response to ICI as well as to conventional therapies (chemotherapy, radiotherapy, targeted therapy, and surgery) in cancer patients.

Pan-cancer analysis of CDKN2A alterations identifies a subset of gastric cancer with a cold tumor immune microenvironment.

BACKGROUND: Although CDKN2A alteration has been explored as a favorable factor for tumorigenesis in pan-cancers, the association between CDKN2A point mutation (MUT) and intragenic deletion (DEL) and response to immune checkpoint inhibitors (ICIs) is still disputed. This study aims to determine the associations of CDKN2A MUT and DEL with overall survival (OS) and response to immune checkpoint inhibitors treatment (ICIs) among pan-cancers and the clinical features of CDKN2A-altered gastric cancer. METHODS: This study included 45,000 tumor patients that underwent tumor sequencing across 33 cancer types from four cohorts, the MSK-MetTropism, MSK-IMPACT, OrigiMed2020 and TCGA cohorts. Clinical outcomes and genomic factors associated with response to ICIs, including tumor mutational burden, copy number alteration, neoantigen load, microsatellite instability, tumor immune microenvironment and immune-related gene signatures, were collected in pan-cancer. Clinicopathologic features and outcomes were assessed in gastric cancer. Patients were grouped based on the presence of CDKN2A wild type (WT), CDKN2A MUT, CDKN2A DEL and CDKN2A other alteration (ALT). RESULTS: Our research showed that CDKN2A-MUT patients had shorter survival times than CDKN2A-WT patients in the MSK MetTropism and TCGA cohorts, but longer OS in the MSK-IMPACT cohort with ICIs treatment, particularly in patients having metastatic disease. Similar results were observed among pan-cancer patients with CDKN2A DEL and other ALT. Notably, CDKN2A ALT frequency was positively related to tumor-specific objective response rates to ICIs in MSK MetTropism and OrigiMed 2020. Additionally, individuals with esophageal carcinoma or stomach adenocarcinoma who had CDKN2A MUT had poorer OS than patients from the MSK-IMPACT group, but not those with adenocarcinoma. We also found reduced levels of activated NK cells, T cells CD8 and M2 macrophages in tumor tissue from CDKN2A-MUT or DEL pan-cancer patients compared to CDKN2A-WT patients in TCGA cohort. Gastric cancer scRNA-seq data also showed that CDKN2A-ALT cancer contained less CD8 T cells but more exhausted T cells than CDKN2A-WT cancer. A crucial finding of the pathway analysis was the inhibition of three immune-related pathways in the CDKN2A ALT gastric cancer patients, including the interferon alpha response, inflammatory response, and interferon gamma response. CONCLUSIONS: This study illustrates the CDKN2A MUT and DEL were associated with a poor outcome across cancers. CDKN2A ALT, on the other hand, have the potential to be used as a biomarker for choosing patients for ICI treatment, notably in esophageal carcinoma and stomach adenocarcinoma.

Metabolic reprogramming-driven homologous recombination and TCA cycle dysregulation contribute to poor prognoses in lung adenocarcinoma.

Increasing evidence has shown that homologous recombination (HR) and metabolic reprogramming are essential for cellular homeostasis. These two processes are independent as well as closely intertwined. Nevertheless, they have rarely been reported in lung adenocarcinoma (LUAD). We analysed the genomic, immune microenvironment and metabolic microenvironment features under different HR activity states. Using cell cycle, EDU and cell invasion assays, we determined the impacts of si-SHFM1 on the LUAD cell cycle, proliferation and invasion. The levels of isocitrate dehydrogenase (IDH) and α-ketoglutarate dehydrogenase (α-KGDH) were determined by ELISA in the NC and si-SHFM1 groups of A549 cells. Finally, cell samples were used to extract metabolites for HPIC-MS/MS to analyse central carbon metabolism. We found that high HR activity was associated with a poor prognosis in LUAD, and HR was an independent prognostic factor for TCGA-LUAD patients. Moreover, LUAD samples with a high HR activity presented low immune infiltration levels, a high degree of genomic instability, a good response status to immune checkpoint blockade therapy and a high degree of drug sensitivity. The si-SHFM1 group presented a significantly higher proportion of cells in the G0/G1 phase, lower levels of DNA replication, and significantly lower levels of cell migration and both TCA enzymes. Our current results indicated that there is a strong correlation between HR and the TCA cycle in LUAD. The TCA cycle can promote SHFM1-mediated HR in LUAD, raising their activities, which can finally result in a poor prognosis and impair immunotherapeutic efficacy.

Lymphocyte counts predict optimal timing of chemotherapy reinitiation after antivirus treatment for herpes zoster in children with leukemia.

Herpes zoster (HZ) is rare in healthy children, but more prevalent in those with leukemia. Optimal timing of chemotherapy reinitiation after HZ treatment is challenging because chemotherapy suppresses immunity and increases risk of HZ relapse. We aimed to optimize the timing of chemotherapy reinitiation after HZ therapy in children with leukemia. The study included 31 children with acute leukemia and HZ infection. General information, clinical symptoms, laboratory test results, duration of HZ treatment, and prognosis were compared with those of children with leukemia alone. Correlation analysis was performed for 20 children who restarted chemotherapy after HZ treatment. Of 31 children with leukemia and HZ, 67.74% had lesions at multiple sites. The median time from chemotherapy initiation to HZ onset was 14.1 (1.5-29.5) months. Among 27 children included in the follow-up, there was one case of HZ relapse. After excluding children who did not continue chemotherapy after HZ treatment, the median interval between completion of HZ therapy and chemotherapy reinitiation in the remaining 20 children was 8.00 (- 3 to 27) days. Lymphocyte counts (LY#) on restarting chemotherapy correlated inversely with HZ lesion healing time (p < 0.05). LY# at the time of HZ onset were lower than those pre- and post-onset, and lower than those in the control group (p < 0.05). In conclusion, children with leukemia have a good HZ prognosis, but an increased risk of HZ recurrence. LY# at the time of chemotherapy reinitiation may be a useful indicator for selecting the optimal interval between antiviral therapy completion and chemotherapy reinitiation.

ANXA5: A Key Regulator of Immune Cell Infiltration in Hepatocellular Carcinoma.

BACKGROUND Hepatocellular carcinoma (HCC) poses a significant threat to human life and is the most prevalent form of liver cancer. The intricate interplay between apoptosis, a common form of programmed cell death, and its role in immune regulation stands as a crucial mechanism influencing tumor metastasis. MATERIAL AND METHODS Utilizing HCC samples from the TCGA database and 61 anoikis-related genes (ARGs) sourced from GeneCards, we analyzed the relationship between ARGs and immune cell infiltration in HCC. Subsequently, we identified long non-coding RNAs (lncRNAs) associated with ARGs, using the least absolute shrinkage and selection operator (LASSO) regression analysis to construct a robust prognostic model. The predictive capabilities of the model were then validated through examination in a single-cell dataset. RESULTS Our constructed prognostic model, derived from lncRNAs linked to ARGs, comprised 11 significant lncRNAs: NRAV, MCM3AP-AS1, OTUD6B-AS1, AC026356.1, AC009133.1, DDX11-AS1, AC108463.2, MIR4435-2HG, WARS2-AS1, LINC01094, and HCG18. The risk score assigned to HCC samples demonstrated associations with immune indicators and the infiltration of immune cells. Further, we identified Annexin A5 (ANXA5) as the pivotal gene among ARGs, with it exerting a prominent role in regulating the lncRNA gene signature. Our validation in a single-cell database elucidated the involvement of ANXA5 in immune cell infiltration, specifically in the regulation of mononuclear cells. CONCLUSIONS This study delves into the intricate correlation between ARGs and immune cell infiltration in HCC, culminating in the development of a novel prognostic model reliant on 11 ARGs-associated lncRNAs. Furthermore, our findings highlight ANXA5 as a promising target for immune regulation in HCC, offering new perspectives for immune therapy in the context of HCC.

Time In Tight Range in children and adolescents with type 1 diabetes: A cross-sectional observational single centre study evaluating efficacy of new advanced technologies.

INTRODUCTION: Early and tight glycaemic control is crucial to prevent long-term complications of Type 1 Diabetes (T1D). The aim of our study was to compare glucose metrics, including Time In Tight Range (TITR), in a real-world setting. METHODS: We performed a single-centre cross-sectional study in 534 children and adolescents with T1D. Participants were divided into four groups (multiple daily injections + real-time Continuous glucose monitoring (CGM), multiple daily injections + intermittently scanned CGM, sensor augmented pump (SAP), and Advanced Hybrid Closed-Loop (AHCL). Demographical and clinical data were collected and analysed. RESULTS: The group with AHCL showed significantly higher Time In Range (TIR) (71.31% ± 10.88) than SAP (57.82% ± 14.98; p < 0.001), MDI + rtCGM (54.56% ± 17.04; p < 0.001) and MDI + isCGM (52.17% ± 19.36; p < 0.001) groups with a lower Time Above Range (p < 0.001). The group with AHCL also showed lower Time Below Range than MDI + isCGM and SAP groups (p < 0.01). The overall TITR was 37% ± 14 with 19% of participants who reached a TITR ≥50% with a mean TIR of 81%. AHCL had significantly higher TITR (45.46% ± 11.77) than SAP (36.25% ± 13.53; p < 0.001), MDI + rtCGM (34.03% ± 13.89; p < 0.001) and MDI + isCGM (33.37% ± 15.84; p < 0.001) groups with a lower Coefficient of Variation (p < 0.001). CONCLUSIONS: Our study indicates that AHCL ensures a better glycaemic control with an improvement in both TIR and TITR, along with a reduction in CV. Implementation of automated insulin delivery systems should be considered in the treatment of children and adolescents with T1D.

Risk factor analysis and nomogram for predicting poor symptom control in smoking asthmatics.

BACKGROUND: Smoking induces and modifies the airway immune response, accelerating the decline of asthmatics' lung function and severely affecting asthma symptoms' control level. To assess the prognosis of asthmatics who smoke and to provide reasonable recommendations for treatment, we constructed a nomogram prediction model. METHODS: General and clinical data were collected from April to September 2021 from smoking asthmatics aged ≥14 years attending the People's Hospital of Zhengzhou University. Patients were followed up regularly by telephone or outpatient visits, and their medication and follow-up visits were recorded during the 6-months follow-up visit, as well as their asthma control levels after 6 months (asthma control questionnaire-5, ACQ-5). The study employed R4.2.2 software to conduct univariate and multivariate logistic regression analyses to identify independent risk factors for 'poorly controlled asthma' (ACQ>0.75) as the outcome variable. Subsequently, a nomogram prediction model was constructed. Internal validation was used to test the reproducibility of the model. The model efficacy was evaluated using the consistency index (C-index), receiver operating characteristic (ROC) curve, calibration curve, and decision curve. RESULTS: Invitations were sent to 231 asthmatics who smoked. A total of 202 participants responded, resulting in a final total of 190 participants included in the model development. The nomogram established five independent risk factors (P<0.05): FEV1%pred, smoking index (100), comorbidities situations, medication regimen, and good or poor medication adherence. The area under curve (AUC) of the modeling set was 0.824(95%CI 0.765-0.884), suggesting that the nomogram has a high ability to distinguish poor asthma control in smoking asthmatics after 6 months. The calibration curve showed a C-index of 0.824 for the modeling set and a C-index of 0.792 for the self-validation set formed by 1000 bootstrap sampling, which means that the prediction probability of the model was consistent with reality. Decision curve analysis (DCA) of the nomogram revealed that the net benefit was higher when the risk threshold probability for poor asthma control was 4.5 - 93.9%. CONCLUSIONS: FEV1%pred, smoking index (100), comorbidities situations, medication regimen, and medication adherence were identified as independent risk factors for poor asthma control after 6 months in smoking asthmatics. The nomogram established based on these findings can effectively predict relevant risk and provide clinicians with a reference to identify the poorly controlled population with smoking asthma as early as possible, and to select a better therapeutic regimen. Meanwhile, it can effectively improve the medication adherence and the degree of attention to complications in smoking asthma patients.

Prognostic effect of triglyceride glucose-related parameters on all-cause and cardiovascular mortality in the United States adults with metabolic dysfunction-associated steatotic liver disease.

BACKGROUNDS: Insulin resistance (IR) plays a vital role in the pathogenesis of the metabolic dysfunction-associated steatotic liver disease (MASLD). However, it remains unclear whether triglyceride-glucose (TyG) related parameters, which serve as useful biomarkers to assess IR, have prognostic effects on mortality outcomes of MASLD. METHODS: Participants in the National Health and Nutrition Examination Survey (NHANES) database from 1999 to 2018 years were included. TyG and its related parameters [TyG-waist circumference (TyG-WC) and TyG-waist to height ratio (TyG-WHtR)] were calculated. Kaplan-Meier curves, Cox regression analysis, and restricted cubic splines (RCS) were conducted to evaluate the association between TyG-related indices with the all-cause and cardiovascular mortality of adults with MASLD. The concordance index (C-index) was used to evaluate the prediction accuracy of TyG-related indices. RESULTS: A total of 8208 adults (4209 men and 3999 women, median age 49.00 years) with MASLD were included in this study. Multivariate-adjusted Cox regression analysis revealed that high quartile levels of TyG-related indices were significantly associated with the all-cause mortality of participants with MASLD [TyGadjusted hazard ratio (aHR) = 1.25, 95% confidence interval (CI) 1.05-1.50, P = 0.014; TyG-WCaHR for all-cause mortality = 1.28, 95% CI 1.07-1.52, P = 0.006; TyG-WHtRaHR for all-cause mortality = 1.50, 95% CI 1.25-1.80, P < 0.001; TyG-WCaHR for cardiovascular mortality = 1.81, 95% CI 1.28-2.55, P = 0.001; TyG-WHtRaHR for cardiovascular mortality = 2.22, 95% CI 1.55-3.17, P < 0.001]. The C-index of TyG-related indices for predicting all-cause mortality was 0.563 for the TyG index, 0.579 for the TyG-WC index, and 0.585 for the TyG-WHtR index, respectively. Regarding cardiovascular mortality, the C-index was 0.561 for the TyG index, 0.607 for the TyG-WC index, and 0.615 for the TyG-WHtR index, respectively. Nonlinear trends were observed between TyG and TyG-WC indices with all-cause mortality of MASLD (P < 0.001 and = 0.012, respectively). A non-linear relationship was observed between the TyG index and cardiovascular mortality of MASLD (P = 0.025). Subgroup analysis suggested that adults aged < 65 years old and those without comorbidities were more sensitive to the mortality prediction of TyG-related indices. CONCLUSION: Findings of this study highlight the predictive value of TyG-related indices, especially the TyG-WHtR index, in the mortality outcomes of adults with MASLD. TyG-related indices would be surrogate biomarkers for the clinical management of MASLD.

Transcriptomic and genomic characteristics of intrahepatic metastases of primary liver cancer.

BACKGROUND: Patients with primary multifocal hepatocellular carcinoma (HCC) have a poor prognosis and often experience a high rate of treatment failure. Multifocal HCC is mainly caused by intrahepatic metastasis (IM), and though portal vein tumor thrombosis (PVTT) is considered a hallmark of IM, the molecular mechanism by which primary HCC cells invade the portal veins remains unclear. Therefore, it is necessary to recognize the early signs of metastasis of HCC to arrange better treatment for patients. RESULTS: To determine the differential molecular features between primary HCC with and without phenotype of metastasis, we used the CIBERSORTx software to deconvolute cell types from bulk RNA-Seq based on a single-cell transcriptomic dataset. According to the relative abundance of tumorigenic and metastatic hepatoma cells, VEGFA+ macrophages, effector memory T cells, and natural killer cells, HCC samples were divided into five groups: Pro-T, Mix, Pro-Meta, NKC, and MemT, and the transcriptomic and genomic features of the first three groups were analyzed. We found that the Pro-T group appeared to retain native hepatic metabolic activity, whereas the Pro-Meta group underwent dedifferentiation. Genes highly expressed in the group Pro-Meta often signify a worse outcome. CONCLUSIONS: The HCC cohort can be well-typed and prognosis predicted according to tumor microenvironment components. Primary hepatocellular carcinoma may have obtained corresponding molecular features before metastasis occurred.