Methylation changes of liver DNA during the formation of gallstones.

Aim: To explore the overall methylation changes in liver tissues during the formation of gallstones, as well as the key pathways and genes involved in the process. Methods: Reduced-representation bisulfite sequencing and RNA sequencing were conducted on the liver tissues of mice with gallstones and control normal mice. Results: A total of 8705 differentially methylated regions in CpG and 1410 differentially expressed genes were identified. The joint analysis indicated that aberrant DNA methylation may be associated with dysregulated gene expression in key pathways such as cholesterol metabolism and bile secretion. Conclusion: We propose for the first time that methylation changes in some key pathway genes in liver tissue may be involved in the formation of gallstones.

Prediction of human epidermal growth factor receptor 2 (HER2) status in breast cancer by mammographic radiomics features and clinical characteristics: a multicenter study.

OBJECTIVES: To preoperatively evaluate the human epidermal growth factor 2 (HER2) status in breast cancer using mammographic radiomics features and clinical characteristics on a multi-vendor and multi-center basis. METHODS: This multi-center study included a cohort of 1512 Chinese female with invasive ductal carcinoma of no special type (IDC-NST) from two different hospitals and five devices (1332 from Institution A, used for training and testing the models, and 180 women from Institution B, as the external validation cohort). The Gradient Boosting Machine (GBM) was employed to establish radiomics and multiomics models. Model efficacy was evaluated by the area under the curve (AUC). RESULTS: The number of HER2-positive patients in the training, testing, and external validation cohort were 245(26.3%), 105 (26.3.8%), and 51(28.3%), respectively, with no statistical differences among the three cohorts (p = 0.842, chi-square test). The radiomics model, based solely on the radiomics features, achieved an AUC of 0.814 (95% CI, 0.784-0.844) in the training cohort, 0.776 (95% CI, 0.727-0.825) in the testing cohort, and 0.702 (95% CI, 0.614-0.790) in the external validation cohort. The multiomics model, incorporated radiomics features with clinical characteristics, consistently outperformed the radiomics model with AUC values of 0.838 (95% CI, 0.810-0.866) in the training cohort, 0.788 (95% CI, 0.741-0.835) in the testing cohort, and 0.722 (95% CI, 0.637-0.811) in the external validation cohort. CONCLUSIONS: Our study demonstrates that a model based on radiomics features and clinical characteristics has the potential to accurately predict HER2 status of breast cancer patients across multiple devices and centers. CLINICAL RELEVANCE STATEMENT: By predicting the HER2 status of breast cancer reliably, the presented model built upon radiomics features and clinical characteristics on a multi-vendor and multi-center basis can help in bolstering the model's applicability and generalizability in real-world clinical scenarios. KEY POINTS: • The mammographic presentation of breast cancer is closely associated with the status of human epidermal growth factor receptor 2 (HER2). • The radiomics model, based solely on radiomics features, exhibits sub-optimal performance in the external validation cohort. • By combining radiomics features and clinical characteristics, the multiomics model can improve the prediction ability in external data.

Bacteria-Based Nanoprobes for Cancer Therapy.

Surgical removal together with chemotherapy and radiotherapy has used to be the pillars of cancer treatment. Although these traditional methods are still considered as the first-line or standard treatments, non-operative situation, systemic toxicity or resistance severely weakened the therapeutic effect. More recently, synthetic biological nanocarriers elicited substantial interest and exhibited promising potential for combating cancer. In particular, bacteria and their derivatives are omnipotent to realize intrinsic tumor targeting and inhibit tumor growth with anti-cancer agents secreted and immune response. They are frequently employed in synergistic bacteria-mediated anticancer treatments to strengthen the effectiveness of anti-cancer treatment. In this review, we elaborate on the development, mechanism and advantage of bacterial therapy against cancer and then systematically introduce the bacteria-based nanoprobes against cancer and the recent achievements in synergistic treatment strategies and clinical trials. We also discuss the advantages as well as the limitations of these bacteria-based nanoprobes, especially the questions that hinder their application in human, exhibiting this novel anti-cancer endeavor comprehensively.

Heatwave characteristics complicate the association between PM2.5 components and schizophrenia hospitalizations in a changing climate: Leveraging of the individual residential environment.

BACKGROUND: In the era characterized by global environmental and climatic changes, understanding the effects of PM2.5 components and heatwaves on schizophrenia (SCZ) is essential for implementing environmental interventions at the population level. However, research in this area remains limited, which highlights the need for further research and effort. We aim to assess the association between exposure to PM2.5 components and hospitalizations for SCZ under different heatwave characteristics. METHODS: We conducted a 16 municipalities-wide, individual exposure-based, time-stratified, case-crossover study from January 1, 2017, to December 31, 2020, encompassing 160736 hospitalizations in Anhui Province, China. Daily concentrations of PM2.5 components were obtained from the Tracking Air Pollution in China dataset. Conditional logistic regression models were used to investigate the association between PM2.5 components and hospitalizations. Additionally, restricted cubic spline models were used to identify protective thresholds of residential environment in response to environmental and climate change. RESULTS: Our findings indicate a positive correlation between PM2.5 and its components and hospitalizations. Significantly, a 1 µg/m3 increase in black carbon (BC) was associated with the highest risk, at 1.58% (95%CI: 0.95-2.25). Exposure to heatwaves synergistically enhanced the impact of PM2.5 components on hospitalization risks, and the interaction varied with the intensity and duration of heatwaves. Under the 99th percentile heatwave events, the impact of PM2.5 and its components on hospitalizations was most pronounced, which were PM2.5 (2-4d: 4.59%, 5.09%, and 5.09%), sulfate (2-4d: 21.73%, 23.23%, and 25.25%), nitrate (2-4d: 17.51%, 16.93%, and 20.31%), ammonium (2-4d: 27.49%, 31.03%, and 32.41%), organic matter (2-4d: 32.07%, 25.42%, and 24.48%), and BC (2-4d: 259.36%, 288.21%, and 152.52%), respectively. Encouragingly, a protective effect was observed when green and blue spaces comprised more than 17.6% of the residential environment. DISCUSSION: PM2.5 components and heatwave exposure were positively associated with an increased risk of hospitalizations, although green and blue spaces provided a mitigating effect.

Meningioma consistency assessment based on the fusion of deep learning features and radiomics features.

PURPOSE: This study aims to combine deep learning features with radiomics features for the computer-assisted preoperative assessment of meningioma consistency. METHODS: 202 patients with surgery and pathological diagnosis of meningiomas at our institution between December 2016 and December 2018 were retrospectively included in the study. The T2-fluid attenuated inversion recovery (T2-Flair) images were evaluated to classify meningioma as soft or hard by professional neurosurgeons based on Zada's consistency grading system. All the patients were split randomly into a training cohort (n = 162) and a testing cohort (n = 40). A convolutional neural network (CNN) model was proposed to extract deep learning features. These deep learning features were combined with radiomics features. After multiple feature selections, selected features were used to construct classification models using four classifiers. AUC was used to evaluate the performance of each classifier. A signature was further constructed by using the least absolute shrinkage and selection operator (LASSO). A nomogram based on the signature was created for predicting meningioma consistency. RESULTS: The logistic regression classifier constructed using 17 radiomics features and 9 deep learning features provided the best performance with a precision of 0.855, a recall of 0.854, an F1-score of 0.852 and an AUC of 0.943 (95 % CI, 0.873-1.000) in the testing cohort. The C-index of the nomogram was 0.822 (95 % CI, 0.758-0.885) in the training cohort and 0.943 (95 % CI, 0.873-1.000) in the testing cohort with good calibration. Decision curve analysis further confirmed the clinical usefulness of the nomogram for predicting meningioma consistency. CONCLUSIONS: The proposed method for assessing meningioma consistency based on the fusion of deep learning features and radiomics features is potentially clinically valuable. It can be used to assist physicians in the preoperative determination of tumor consistency.

Green space and its types can attenuate the associations of PM2.5 and its components with prediabetes and diabetes-- a multicenter cross-sectional study from eastern China.

BACKGROUND: The effect of fine particulate matter (PM2.5) components on prediabetes and diabetes is of concern, but the evidence is limited and the specific role of different green space types remains unclear. This study aims to investigate the relationship of PM2.5 and its components with prediabetes and diabetes as well as the potential health benefits of different types and combinations of green spaces. METHODS: A multicenter cross-sectional study was conducted in eastern China by using a multi-stage random sampling method. Health screening and questionnaires for 98,091 participants were performed during 2017-2020. PM2.5 and its five components were estimated by the inverse distance weighted method, and green space was reflected by the Normalized Difference Vegetation Index (NDVI), percentages of tree or grass cover. Multivariate logistic regression and quantile g-computing were used to explore the associations of PM2.5 and five components with prediabetes and diabetes and to elucidate the potential moderating role of green space and corresponding type combinations in these associations. RESULTS: Each interquartile range (IQR) increment of PM2.5 was associated with both prediabetes (odds ratio [OR]: 1.15, 95%CI [confidence interval]: 1.10-1.20) and diabetes (OR: 1.18, 95% CI: 1.11-1.25), respectively. All five components of PM2.5 were related to prediabetes and diabetes. The ORs of PM2.5 on diabetes were 1.49 (1.35-1.63) in the low tree group and 0.90 (0.82-0.98) in the high tree group, respectively. In the high tree-high grass group, the harmful impacts of PM2.5 and five components were significantly lower than in the other groups. CONCLUSION: Our study suggested that PM2.5 and its components were associated with the increased risk of prediabetes and diabetes, which could be diminished by green space. Furthermore, the coexistence of high levels of tree and grass cover provided greater benefits. These findings had critical implications for diabetes prevention and green space-based planning for healthy city.

Urolithin B Attenuates Cerebral Ischemia-reperfusion Injury by Modulating Nrf2-regulated Anti-oxidation in Rats.

Ischemia-reperfusion (IR) induces a wide range of irreversible injuries. Cerebral IR injury (IRI) refers to additional brain tissue damage that occurs after blood flow is restored following cerebral ischemia. Currently, no established methods exist for treating IRI. Oxidative stress is recognized as a primary mechanism initiating IRI and a crucial focal target for its treatment. Urolithin B, a metabolite derived from ellagitannins, antioxidant polyphenols, has demonstrated protective effects against oxidative stress in various disease conditions. However, the precise mechanism underlying UB's effect on IRI remains unclear. In our current investigation, we assessed UB's ability to mitigate neurological functional impairment induced by IR using a neurological deficit score. Additionally, we examined cerebral infarction following UB administration through TTC staining and neuron Nissl staining. UB's inhibition of neuronal apoptosis was demonstrated through the TUNEL assay and Caspase-3 measurement. Additionally, we examined UB's effect on oxidative stress levels by analyzing malondialdehyde (MDA) concentration, superoxide dismutase (SOD) activity, and immunohistochemistry analysis of inducible nitric oxide synthase (iNOS) and 8-hydroxyl-2'-deoxyguanosine (8-OHdG). Notably, UB demonstrated a reduction in oxidative stress levels. Mechanistically, UB was found to stimulate the Nrf2/HO-1 signaling pathway, as evidenced by the significant reduction in UB's neuroprotective effects upon administration of ATRA, an Nrf2 inhibitor. In summary, UB effectively inhibits oxidative stress induced by IR through the activation of the Nrf2/HO-1 signaling pathway. These findings suggest that UB holds promise as a therapeutic agent for the treatment of IRI.

Distinct MRI characteristics of spinal cord diffuse midline glioma, H3 K27-altered in comparison to spinal cord glioma without H3 K27-alteration and demyelination disorder.

BACKGROUND: An applicable magnetic resonance imaging (MRI) biomarker for diffuse midline glioma (DMG), H3 K27-altered of the spinal cord is important for non-invasive diagnosis. PURPOSE: To evaluate the efficacy of conventional MRI (cMRI) in distinguishing between DMGs, H3 K27-altered, gliomas without H3 K27-alteration, and demyelinating lesions in the spinal cord. MATERIAL AND METHODS: Between January 2017 and February 2023, patients with pathology-confirmed spinal cord gliomas (including ependymomas) with definite H3 K27 status and demyelinating diseases diagnosed by recognized criteria were recruited as the training set for this retrospective study. Morphologic parameter assessment was performed by two neuroradiologists on T1-weighted, T2-weighted, and contrast-enhanced T1-weighted imaging. Variables with high inter- and intra-observer agreement were included in univariable correlation analysis and multivariable logistic regression. The performance of the final model was verified by internal and external testing sets. RESULTS: The training cohort included 21 patients with DMGs (13 men; mean age = 34.57 ± 13.489 years), 21 with wild-type gliomas (10 men; mean age = 46.76 ± 17.017 years), and 20 with demyelinating diseases (5 men; mean age = 49.50 ± 18.872 years). A significant difference was observed in MRI features, including cyst(s), hemorrhage, pial thickening with enhancement, and the maximum anteroposterior diameter of the spinal cord. The prediction model, integrating age, age2, and morphological characteristics, demonstrated good performance in the internal and external testing cohort (accuracy: 0.810 and 0.800, specificity: 0.810 and 0.720, sensitivity: 0.872 and 0.849, respectively). CONCLUSION: Based on cMRI, we developed a model with good performance for differentiating among DMGs, H3 K27-altered, wild-type glioma, and demyelinating lesions in the spinal cord.

Comprehensive Analysis of Disulfidptosis-Related LncRNAs in Molecular Classification, Immune Microenvironment Characterization and Prognosis of Gastric Cancer.

BACKGROUND: Disulfidptosis is a novel form of programmed cell death that unveils promising avenues for the exploration of tumor treatment modalities. Gastric cancer (GC) is a malignant tumor characterized by high incidence and mortality rate. However, there has been no systematic study of disulfidptosis-related long noncoding RNAs (DRLs) signature in GC patients. METHODS: The lncRNA expression profiles containing 412 GC samples were acquired from the Cancer Genome Atlas (TCGA) database. Differential expression analysis was performed alongside Pearson correlation analysis to identify DRLs. Prognostically significant DRLs were further screened using univariate COX regression analysis. Subsequently, LASSO regression and multifactorial COX regression analyses were employed to establish a risk signature composed of DRLs that exhibit independent prognostic significance. The predictive value of this risk signature was further validated in a test cohort. The ESTIMATE, CIBERSORT and ssGSEA methodologies were utilized to investigate the tumor immune microenvironment of GC populations with different DRLs profiles. Finally, the correlation between DRLs and various GC drug responses was explored. RESULTS: We established a prognostic signature comprising 12 disulfidptosis-related lncRNAs (AC110491.1, AL355574.1, RHPN1-AS1, AOAH-IT1, AP001065.3, MEF2C-AS1, AC016394.2, LINC00705, LINC01952, PART1, TNFRSF10A-AS1, LINC01537). The Kaplan-Meier survival analysis revealed that patients in the high-risk group exhibited a poor prognosis. Both univariate and multivariate COX regression models demonstrated that the DRLs signature was an independent prognostic indicator in GC patients. Furthermore, the signature exhibited accurate predictions of survival at 1-, 3- and 5- years with the area under the curve (AUC) values of 0.708, 0.689 and 0.854, respectively. In addition, we also observed significant associations between the DRLs signature and various clinical variables, distinct immune landscape and drug sensitivity profiles in GC patients. The low-risk group patients may be more likely to benefit from immunotherapy and chemotherapy. CONCLUSIONS: Our study investigated the role and potential clinical implications of DRLs in GC. The risk model constructed by DRLs demonstrated high accuracy in predicting the survival outcomes of GC and improving the treatment efficacy for GC patients.

Multicenter Study of the Utility of Convolutional Neural Network and Transformer Models for the Detection and Segmentation of Meningiomas.

PURPOSE: This study aimed to investigate the effectiveness and practicality of using models like convolutional neural network and transformer in detecting and precise segmenting meningioma from magnetic resonance images. METHODS: The retrospective study on T1-weighted and contrast-enhanced images of 523 meningioma patients from 3 centers between 2010 and 2020. A total of 373 cases split 8:2 for training and validation. Three independent test sets were built based on the remaining 150 cases. Six convolutional neural network detection models trained via transfer learning were evaluated using 4 metrics and receiver operating characteristic analysis. Detected images were used for segmentation. Three segmentation models were trained for meningioma segmentation and were evaluated via 4 metrics. In 3 test sets, intraclass consistency values were used to evaluate the consistency of detection and segmentation models with manually annotated results from 3 different levels of radiologists. RESULTS: The average accuracies of the detection model in the 3 test sets were 97.3%, 93.5%, and 96.0%, respectively. The model of segmentation showed mean Dice similarity coefficient values of 0.884, 0.834, and 0.892, respectively. Intraclass consistency values showed that the results of detection and segmentation models were highly consistent with those of intermediate and senior radiologists and lowly consistent with those of junior radiologists. CONCLUSIONS: The proposed deep learning system exhibits advanced performance comparable with intermediate and senior radiologists in meningioma detection and segmentation. This system could potentially significantly improve the efficiency of the detection and segmentation of meningiomas.

PINK1-mediated mitophagy induction protects against preeclampsia by decreasing ROS and trophoblast pyroptosis.

INTRODUCTION: Preeclampsia (PE) is a multisystemic disorder attributed to the excessive presentation of placenta-derived immunoinflammatory factors. PTEN-induced putative kinase 1 (PINK1)-mediated mitophagy participates in the development and persistence of the inflammation. We hypothesized that dysregulated mitophagy might be involved in the pathogenesis of PE by promoting the activation of trophoblast pyroptosis that augment inflammation. METHODS: The morphology of mitochondrial in placenta were observed by transmission electron microscopy. The localization of PINK1 in the placenta was determined by immunohistochemistry. The expression levels of PINK1, PARKIN, LC3B, and SQSTM1 and pyroptosis-related molecules were compared between normal pregnancies and PE. We used hypoxia/reoxygenation (H/R) to stimulate the trophoblast hypoxia environment. HTR-8/SVneo cells were transfected with PINK1 plasmid and si-PINK1, respectively, and then were treated with H/R, to determine whether PINK1 regulated ROS and HTR-8/Svneo pyroptosis. Finally, ROS production was inhibited by MitoTEMPO to observe whether the pro-pyroptosis effect of PINK1 knockdown is alleviated. RESULTS: Swollen mitochondrial were accumulated in the PE placentae. PINK1 is localized on villus trophoblast (VTs) and extravillous trophoblast (EVTs). PINK1-mediated mitophagy was abolished in the PE placenta, while the levels of pyroptosis were induced. H/R stimulation aggravated the downregulation of mitophagy and the up-regulation of pyroptosis. Overexpression of PINK1 mitigated H/R-induced upregulation of ROS and pyroptosis while silencing PINK1 did the opposite. Reducing ROS production can effectively resist the pro-pyroptosis effect of PINK1 knockdown. DISCUSSION: This study demonstrated that PINK1-mediated mitophagy might played a protective role in PE by reducing ROS and trophoblast pyroptosis.

AP4M1 as a prognostic biomarker associated with cell proliferation, migration and immune regulation in hepatocellular carcinoma.

BACKGROUND: AP4M1 is a protein-coding gene that plays a crucial role in transporter activity, recognition, and hereditary-associated diseases, but it's largely unknown in cancers. METHODS: The expression level of AP4M1 in cancers was investigated by The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases, and the correlation between AP4M1 and hepatocellular carcinoma (HCC) clinicopathological parameters were analyzed. Univariate and multifactorial COX regression analyses were performed to clarify the prognostic value of AP4M1 in HCC. The correlation between AP4M1 and immune cell infiltration was analyzed using single-sample Gene Set Enrichment Analysis (ssGSEA). Besides, we verified the biological function of AP4M1 by applying Cell Counting Kit-8 (CCK8), colony formation, and transwell assays. RESULTS: The expression of AP4M1 was significantly elevated in HCC and was correlated with patients' pathological grades, AFP, and BMI. Kaplan-Meier survival curves indicated that patients with AP4M1 overexpression had worse overall survival. Univariate and multivariate COX regression analyses showed that AP4M1 was an independent risk factor affecting the prognosis of HCC. In addition, we observed that AP4M1 positively correlated with most immune checkpoint suppressor genes in HCC. Moreover, in vitro experiments further confirmed that AP4M1 could promote the proliferation and invasion of HCC. CONCLUSIONS: AP4M1 is highly expressed and associated with poor prognosis in HCC. AP4M1 is closely related to cancer-immune regulation and could be a novel target for HCC, and guiding new strategies for the diagnosis and treatment of HCC patients.

Association of outdoor artificial light at night with metabolic syndrome and the modifying effect of tree and grass cover.

BACKGROUND: Epidemiological studies show that outdoor artificial light at night (ALAN) is linked to metabolic hazards, but its association with metabolic syndrome (MetS) remains unclear. We aimed to investigate the association of outdoor ALAN with MetS in middle-aged and elderly Chinese. METHODS: From 2017-2020, we conducted a cross-sectional study in a total of 109,452 participants living in ten cities of eastern China. MetS was defined by fasting blood glucose (FG), triglyceride (TG), high-density lipoprotein cholesterol (HDL-C), blood pressure (BP), and waist circumference (WC). In 2021, we followed up 4395 participants without MetS at the baseline. Each participant's five-year average exposure to outdoor ALAN, as well as their exposure to green space type, were measured through matching to their address. Generalized linear models were used to assess the associations of outdoor ALAN with MetS. Stratified analyses were performed by sex, age, region, physical activity, and exposure to green space. RESULTS: In the cross-sectional study, compared to the first quantile (Q1) of outdoor ALAN exposure, the odds ratios (ORs) of MetS were 1.156 [95 % confidence interval (CI): 1.111-1.203] and 1.073 (95 %CI: 1.021-1.128) respectively in the third and fourth quantiles (Q3, Q4) of outdoor ALAN exposure. The follow-up study found that, compared to the first quantile (Q1) of outdoor ALAN exposure, the OR of MetS in Q4 of ALAN exposure was 1.204 (95 %CI: 1.019-1.422). Adverse associations of ALAN with MetS components, including high FG, high TG, and obesity, were also found. Greater associations of ALAN with MetS were found in males, the elderly, urban residents, those with low frequency of physical activity, and those living in areas with low levels of grass cover and tree cover. CONCLUSIONS: Outdoor ALAN exposure is associated with an increased MetS risk, especially in males, the elderly, urban residents, those lacking physical activity, and those living in lower levels of grass cover and tree cover.

Association between ambient air pollution and thyroid hormones levels: A systematic review and meta-analysis.

BACKGROUND: Growing studies have focused on the effects of ambient air pollution on thyroid hormones (THs), but the results were controversial. Therefore, a systematic review and meta-analysis was conducted by pooling current evidence on this association. METHODS: Four databases were searched for studies examining the associations of particulate matter [diameter ≤10 µm (PM10) or ≤2.5 µm (PM2.5)] and gaseous [sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO)] pollutants with THs levels. Random effects models were used to pool the changes in THs levels with increasing air pollutant concentrations. Subgroup analyses were constructed by region, design, sample size, pollutant concentrations, evaluated methods, and potential risk exposure windows. RESULTS: A total of 14 studies covering 357,226 participants were included in this meta-analysis. The pooled results showed significant associations of exposure to PM2.5, PM10, NO2, SO2, and CO with decreases in free thyroxine (FT4) with percent changes (PC) ranging from -0.593 % to -3.925 %. PM2.5, NO2, and CO were negatively associated with levels of FT4/FT3 (PC: from -0.604 % to -2.975 %). In addition, results showed significant associations of PM2.5 with hypothyroxinemia and high thyroid-stimulating hormone (TSH). Subgroup analyses indicated that PM2.5 and NO2 were significantly associated with FT4 in studies of Chinese, and similar significant findings were found in studies of PM2.5 and FT4/FT3 in areas with higher concentrations of air pollutants and larger samples. PM2.5 exposure in the first trimester was found to be associated with lower FT4 levels in pregnant women. CONCLUSION: Our findings suggest that exposure to air pollution is associated with changes in THs levels. Enhanced management of highly polluted areas, identification of harmful components and sources of PM, and protection from harmful exposures in early pregnancy may be of great public health importance for the population's thyroid function.

The association between greenery type and gut microbiome in schizophrenia: did all greenspaces play the equivalent role?

In recent years, attention has been focused on the benefit of greenspace on mental health, and it is suggested this link may vary with the type of greenspace. More and more studies have emphasized the influence of the gut microbiome on schizophrenia (SCZ). However, the effects of greenspaces on the gut microbiota in SCZ and the effect of different types of greenspaces on the gut microbiota remain unclear. We aim to examine if there were variations in the effects of various greenspace types on the gut microbiome in SCZ. Besides, we sink to explore important taxonomic compositions associated with different greenspace types. We recruited 243 objects with schizophrenia from Anhui Mental Health Center and collected fecal samples for 16Sr RNA gene sequencing. Three types of greenery coverage were calculated with different circular buffers (800, 1500, and 3000 m) corresponding to individual addresses. The association between greenspace and microbiome composition was analyzed with permutational analysis of variance (PERMANOVA). We conducted the linear regression to capture specific gut microbiome taxa associated with greenery coverage. Tree coverage was consistently associated with microbial composition in both 1500 m (R2 = 0.007, P = 0.030) and 3000 m (R2 = 0.007, P = 0.039). In contrast, there was no association with grass cover in any of the buffer zones. In the regression analysis, higher tree coverage was significantly correlated with the relative abundance of several taxa. Among them, tree coverage was positively associated with increased Bifidobacterium longum (ß = 1.069, P = 0.004), which was the dominant composition in the gut microbiota. The relationship between greenspace and gut microbiome in SCZ differed by the type of greenspace. Besides, "tree coverage" may present a dominant effect on the important taxonomic composition. Our findings might provide instructive evidence for the design of urban greenspace to optimize health and well-being in SCZ as well as the whole people.

PAX1 hypomethylation as a prognostic biomarker for radioresistance of cervical cancer.

BACKGROUND: PAX1 gene methylation plays an important role in the development of cervical cancer. However, its prognostic value after radiotherapy for locally advanced cervical cancer is unknown, so this study aimed to investigate the value of PAX1 gene methylation for predicting the sensitivity of radiotherapy for cervical cancer. METHODS: We selected 125 patients with primary cervical cancer who underwent concurrent chemo-radiotherapy as the study population, quantitative methylation-specific polymerase chain reaction (QMSP) was used for detecting PAX1 methylation status of cervical exfoliated cells. Logistic regression model was used to analyze the risk factors associated with the short-term efficacy and to establish a prediction model of radiotherapy sensitivity based on PAX1 gene methylation. Cell viability after radiation of Hela and SiHa cells transfected with PAX1 or control vector was evaluated by CCK8. Furthermore, RNA-Seq analyses identified different expressed genes (DEGs) in PAX1 overexpressed SiHa cells. Gene Ontology (GO) and pathway enrichment analysis was carried out to determine the biological function of DEGs. RESULTS: PAX1 methylation level was associated with HPV16/18-positive rate. PAX1 hypomethylation was found to be a risk factor for tumor residual after chemo-radiotherapy. A nomogram containing the risk factors for PAX1 methylation status, lymph node metastasis, pathological type and tumor size was further constructed to predict the probability of tumor residual after chemo-radiotherapy (AUC = 0.823, 95% CI 0.736-0.910). High PAX1 protein level was more likely to cause radioresistance in both Hela and SiHa cells. Transcriptomic sequencing of PAX1 overexpressed and control cells identified 615 differentially expressed genes, and GO enrichment analysis suggested that PAX1 may be involved in the regulation of signaling receptor activity and response to viruses. CONCLUSION: PAX1 hypomethylation status could be used as a promising biomarker to predict radioresistance in cervical cancer. This further provides a new idea for the individualized treatment strategy of simultaneous radiotherapy for cervical cancer.

The deubiquitinase EIF3H promotes hepatocellular carcinoma progression by stabilizing OGT and inhibiting ferroptosis.

Hepatocellular carcinoma (HCC) is one of the most prevalent and lethal human malignancies, and with quite limited treatment alternatives. The proteasome is responsible for most of the protein degradation in eukaryotic cells and required for the maintenance of intracellular homeostasis. However, its potential role in HCC is largely unknown. In the current study, we identified eukaryotic translation initiation factor 3 subunit H (EIF3H), belonging to the JAB1/MPN/MOV34 (JAMM) superfamily, as a bona fide deubiquitylase of O-GlcNAc transferase (OGT) in HCC. We explored that EIF3H was positively associated with OGT in HCC and was related to the unfavorable prognosis. EIF3H could interact with, deubiquitylate, and stabilize OGT in a deubiquitylase-dependent manner. Specifically, EIF3H was associated with the GT domain of ERα via its JAB/MP domain, thus inhibiting the K48-linked ubiquitin chain on OGT. Besides, we demonstrated that the knockdown of EIF3H significantly reduced OGT protein expression, cell proliferation and invasion, and caused G1/S arrest of HCC. We also found that the deletion of EIF3H prompted ferroptosis in HCC cells. Finally, the effects of EIF3H depletion could be reversed by further OGT overexpression, implying that the OGT status is indispensable for EIF3H function in HCC carcinogenesis. In summary, our study described the oncogenic function of EIF3H and revealed an interesting post-translational mechanism between EIF3H, OGT, and ferroptosis in HCC. Targeting the EIF3H may be a promising approach in HCC. Video Abstract.

The rs17782313 polymorphism near MC4R gene confers a high risk of obesity and hyperglycemia, while PGC1α rs8192678 polymorphism is weakly correlated with glucometabolic disorder: a systematic review and meta-analysis.

Background: The relationships of the rs17782313 polymorphism near melanocortin 4 receptor gene (MC4R) and the rs8192678 polymorphism in peroxisome proliferator-activated receptor gamma coactivator 1 alpha gene (PGC1α) with metabolic abnormalities have been explored in many populations around the world, but the findings were not all consistent and sometimes even a bit contradictory. Methods: Electronic databases including Medline, Scopus, Embase, Web of Science, CNKI and Google Scholar were checked for studies that met the inclusion criteria. Data were carefully extracted from eligible studies. Standardized mean differences (SMDs) were calculated by using a random-effects model to examine the differences in the indexes of obesity, glucometabolic disorder and dyslipidemia between the genotypes of the rs17782313 and rs8192678 polymorphisms. Cochran's Q-statistic test and Begg's test were employed to identify heterogeneity among studies and publication bias, respectively. Results: Fifty studies (58,716 subjects) and 51 studies (18,660 subjects) were respectively included in the pooled meta-analyses for the rs17782313 and rs8192678 polymorphisms. The C-allele carriers of the rs17782313 polymorphism had a higher average level of body mass index (SMD = 0.21 kg/m2, 95% confidence interval [95% CI] = 0.12 to 0.29 kg/m2, p < 0.001), waist circumference (SMD = 0.14 cm, 95% CI = 0.06 to 0.23 cm, p < 0.001) and blood glucose (SMD = 0.09 mg/dL, 95% CI = 0.02 to 0.16 mg/dL, p = 0.01) than the TT homozygotes. Regarding the rs8192678 polymorphism, no significant associations with the indexes of obesity, glucometabolic disorder and dyslipidemia were detected. However, significant correlations between the rs8192678 polymorphism and multiple glucometabolic indexes were observed in subgroup analyses stratified by sex, age, ethnicity and health status. Conclusion: The meta-analysis demonstrates that the C allele of the MC4R rs17782313 polymorphism confers a higher risk of obesity and hyperglycemia, and the PGC1α rs8192678 polymorphism is weakly correlated with glucometabolic disorder. These findings may partly explain the relationships between these variants and diabetes as well as cardiovascular disease. Systematic review registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42022373543.

Glioblastomas with and without peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity present morphological and microstructural differences on conventional MR images.

OBJECTIVES: Glioblastoma (GB) without peritumoral fluid-attenuated inversion recovery (FLAIR) hyperintensity is atypical and its characteristics are barely known. The aim of this study was to explore the differences in pathological and MRI-based intrinsic features (including morphologic and first-order features) between GBs with peritumoral FLAIR hyperintensity (PFH-bearing GBs) and GBs without peritumoral FLAIR hyperintensity (PFH-free GBs). METHODS: In total, 155 patients with pathologically diagnosed GBs were retrospectively collected, which included 110 PFH-bearing GBs and 45 PFH-free GBs. The pathological and imaging data were collected. The Visually AcceSAble Rembrandt Images (VASARI) features were carefully evaluated. The first-order radiomics features from the tumor region were extracted from FLAIR, apparent diffusion coefficient (ADC), and T1CE (T1-contrast enhanced) images. All parameters were compared between the two groups of GBs. RESULTS: The pathological data showed more alpha thalassemia/mental retardation syndrome X-linked (ATRX)-loss in PFH-free GBs compared to PFH-bearing ones (p < 0.001). Based on VASARI evaluation, PFH-free GBs had larger intra-tumoral enhancing proportion and smaller necrotic proportion (both, p < 0.001), more common non-enhancing tumor (p < 0.001), mild/minimal enhancement (p = 0.003), expansive T1/FLAIR ratio (p < 0.001) and solid enhancement (p = 0.009), and less pial invasion (p = 0.010). Moreover, multiple ADC- and T1CE-based first-order radiomics features demonstrated differences, especially the lower intensity heterogeneity in PFH-free GBs (for all, adjusted p < 0.05). CONCLUSIONS: Compared to PFH-bearing GBs, PFH-free ones demonstrated less immature neovascularization and lower intra-tumoral heterogeneity, which would be helpful in clinical treatment stratification. CLINICAL RELEVANCE STATEMENT: Glioblastomas without peritumoral FLAIR hyperintensity show less immature neovascularization and lower heterogeneity leading to potential higher treatment benefits due to less drug resistance and treatment failure. KEY POINTS: • The study explored the differences between glioblastomas with and without peritumoral FLAIR hyperintensity. • Glioblastomas without peritumoral FLAIR hyperintensity showed less necrosis and contrast enhancement and lower intensity heterogeneity. • Glioblastomas without peritumoral FLAIR hyperintensity had less immature neovascularization and lower tumor heterogeneity.