Acod1/itaconate activates Nrf2 in pulmonary microvascular endothelial cells to protect against the obesity-induced pulmonary microvascular endotheliopathy.

BACKGROUND: Obesity is the main risk factor leading to the development of various respiratory diseases, such as asthma and pulmonary hypertension. Pulmonary microvascular endothelial cells (PMVECs) play a significant role in the development of lung diseases. Aconitate decarboxylase 1 (Acod1) mediates the production of itaconate, and Acod1/itaconate axis has been reported to play a protective role in multiple diseases. However, the roles of Acod1/itaconate axis in the PMVECs of obese mice are still unclear. METHODS: mRNA-seq was performed to identify the differentially expressed genes (DEGs) between high-fat diet (HFD)-induced PMVECs and chow-fed PMVECs in mice (|log2 fold change| ≥ 1, p ≤ 0.05). Free fatty acid (FFA) was used to induce cell injury, inflammation and mitochondrial oxidative stress in mouse PMVECs after transfection with the Acod1 overexpressed plasmid or 4-Octyl Itaconate (4-OI) administration. In addition, we investigated whether the nuclear factor erythroid 2-like 2 (Nrf2) pathway was involved in the effects of Acod1/itaconate in FFA-induced PMVECs. RESULTS: Down-regulated Acod1 was identified in HFD mouse PMVECs by mRNA-seq. Acod1 expression was also reduced in FFA-treated PMVECs. Acod1 overexpression inhibited cell injury, inflammation and mitochondrial oxidative stress induced by FFA in mouse PMVECs. 4-OI administration showed the consistent results in FFA-treated mouse PMVECs. Moreover, silencing Nrf2 reversed the effects of Acod1 overexpression and 4-OI administration in FFA-treated PMVECs, indicating that Nrf2 activation was required for the protective effects of Acod1/itaconate. CONCLUSION: Our results demonstrated that Acod1/Itaconate axis might protect mouse PMVECs from FFA-induced injury, inflammation and mitochondrial oxidative stress via activating Nrf2 pathway. It was meaningful for the treatment of obesity-caused pulmonary microvascular endotheliopathy.

Global climate change: Effects of future temperatures on emergency department visits for mental disorders in Beijing, China.

Rising temperatures can increase the risk of mental disorders. As climate change intensifies, the future disease burden due to mental disorders may be underestimated. Using data on the number of daily emergency department visits for mental disorders at 30 hospitals in Beijing, China during 2016-2018, the relationship between daily mean temperature and such visits was assessed using a quasi-Poisson model integrated with a distributed lag nonlinear model. Emergency department visits for mental disorders attributed to temperature changes were projected using 26 general circulation models under four climate change scenarios. Stratification analyses were then conducted by disease subtype, sex, and age. The results indicate that the temperature-related health burden from mental disorders was projected to increase consistently throughout the 21st century, mainly driven by high temperatures. The future temperature-related health burden was higher for patients with mental disorders due to the use of psychoactive substances and schizophrenia as well as for women and those aged <65 years. These findings enhance our knowledge of how climate change could affect mental well-being and can be used to advance and refine targeted approaches to mitigating and adapting to climate change with a view on addressing mental disorders.

Bioinspired Colorimetric Double Inverse Opal Photonic Crystal Indicators for Ethanol Concentration Sensing in Fermentation Engineering.

Photonic crystal-based ethanol concentration indicators with rapid response and brilliant structural color output definitely take a place in colorimetric sensors. Here, based on the H-bond-regulated swelling of acrylate shape memory polymers (SMPs) and the solvent-induced structural color change of the double inverse opal photonic crystals (DIOPCs), new-type photonic crystals (PCs) colorimetric indicators were constructed, exhibiting a span of maximum reflection wavelength (λmax) up to ∼166 nm in response to alcohols with concentrations from 0 to 100 vol %. DIOPC indicators (DIOPCIs) show a rapid response to alcohols (<1.5 s) and output different structural colors (covering from blue to red). The colorimetric sensing mechanism includes the solvent-triggered recovery of the inverse opal skeleton, the cosolvency effect and H-bonds induced swelling/shrinkage of the polymer, the phase separation between polystyrene (PS) microsphere and polymer skeleton, and the light diffraction of DIOPCs. While ensuring a larger λmax span by regulating the H-bond interactions in polymer chains through acrylamide (AAm), AAm-modified DIOPCIs are sensitive to some specific ethanol concentrations. The real-time sensing of ethanol concentration during fermentation verified the practicability of DIOPCIs, thus establishing a visual model between structural color and corresponding fermentation kinetics. We envisage that the DIOPCIs will contribute to the intelligentization of the alcoholic fermentation and distillation industry.

Causal roles of gut microbiota in cholangiocarcinoma etiology suggested by genetic study.

BACKGROUND: Cholangiocarcinoma (CCA) is a highly malignant biliary tract cancer with poor prognosis. Previous studies have implicated the gut microbiota in CCA, but evidence for causal mechanisms is lacking. AIM: To investigate the causal relationship between gut microbiota and CCA risk. METHODS: We performed a two-sample mendelian randomization study to evaluate potential causal associations between gut microbiota and CCA risk using genome-wide association study summary statistics for 196 gut microbial taxa and CCA. Genetic variants were used as instrumental variables. Multiple sensitivity analyses assessed result robustness. RESULTS: Fifteen gut microbial taxa showed significant causal associations with CCA risk. Higher genetically predicted abundance of genus Eubacteriumnodatum group, genus Ruminococcustorques group, genus Coprococcus, genus Dorea, and phylum Actinobacteria were associated with reduced risk of gallbladder cancer and extrahepatic CCA. Increased intrahepatic CCA risk was associated with higher abundance of family Veillonellaceae, genus Alistipes, order Enterobacteriales, and phylum Firmicutes. Protective effects against CCA were suggested for genus Collinsella, genus Eisenbergiella, genus Anaerostipes, genus Paraprevotella, genus Parasutterella, and phylum Verrucomicrobia. Sensitivity analyses indicated these findings were reliable without pleiotropy. CONCLUSION: This pioneering study provides novel evidence that specific gut microbiota may play causal roles in CCA risk. Further experimental validation of these candidate microbes is warranted to consolidate causality and mechanisms.

Deep learning for the automatic detection and segmentation of parotid gland tumors on MRI.

OBJECTIVES: Parotid gland tumors (PGTs) often occur as incidental findings on magnetic resonance images (MRI) that may be overlooked. This study aimed to construct and validate a deep learning model to automatically identify parotid glands (PGs) with a PGT from normal PGs, and in those with a PGT to segment the tumor. MATERIALS AND METHODS: The nnUNet combined with a PG-specific post-processing procedure was used to develop the deep learning model trained on T1-weighed images (T1WI) in 311 patients (180 PGs with tumors and 442 normal PGs) and fat-suppressed (FS)-T2WI in 257 patients (125 PGs with tumors and 389 normal PGs), for detecting and segmenting PGTs with five-fold cross-validation. Additional validation set separated by time, comprising T1WI in 34 and FS-T2WI in 41 patients, was used to validate the model performance. RESULTS AND CONCLUSION: To identify PGs with tumors from normal PGs, using combined T1WI and FS-T2WI, the deep learning model achieved an accuracy, sensitivity and specificity of 98.2% (497/506), 100% (119/119) and 97.7% (378/387), respectively, in the cross-validation set and 98.5% (67/68), 100% (20/20) and 97.9% (47/48), respectively, in the validation set. For patients with PGTs, automatic segmentation of PGTs on T1WI and FS-T2WI achieved mean dice coefficients of 86.1% and 84.2%, respectively, in the cross-validation set, and of 85.9% and 81.0%, respectively, in the validation set. The proposed deep learning model may assist the detection and segmentation of PGTs and, by acting as a second pair of eyes, ensure that incidentally detected PGTs on MRI are not missed.

Diabetes and osteoporosis: a two-sample mendelian randomization study.

BACKGROUND: The effects on bone mineral density (BMD)/fracture between type 1 (T1D) and type 2 (T2D) diabetes are unknown. Therefore, we aimed to investigate the causal relationship between the two types of diabetes and BMD/fracture using a Mendelian randomization (MR) design. METHODS: A two-sample MR study was conducted to examine the causal relationship between diabetes and BMD/fracture, with three phenotypes (T1D, T2D, and glycosylated hemoglobin [HbA1c]) of diabetes as exposures and five phenotypes (femoral neck BMD [FN-BMD], lumbar spine BMD [LS-BMD], heel-BMD, total body BMD [TB-BMD], and fracture) as outcomes, combining MR-Egger, weighted median, simple mode, and inverse variance weighted (IVW) sensitivity assessments. Additionally, horizontal pleiotropy was evaluated and corrected using the residual sum and outlier approaches. RESULTS: The IVW method showed that genetically predicted T1D was negatively associated with TB-BMD (ß = -0.018, 95% CI: -0.030, -0.006), while T2D was positively associated with FN-BMD (ß = 0.033, 95% CI: 0.003, 0.062), heel-BMD (ß = 0.018, 95% CI: 0.006, 0.031), and TB-BMD (ß = 0.050, 95% CI: 0.022, 0.079). Further, HbA1c was not associated with the five outcomes (ß ranged from - 0.012 to 0.075). CONCLUSIONS: Our results showed that T1D and T2D have different effects on BMD at the genetic level. BMD decreased in patients with T1D and increased in those with T2D. These findings highlight the complex interplay between diabetes and bone health, suggesting potential age-specific effects and genetic influences. To better understand the mechanisms of bone metabolism in patients with diabetes, further longitudinal studies are required to explain BMD changes in different types of diabetes.

Androgen signaling inhibits de novo lipogenesis to alleviate lipid deposition in zebrafish.

Testosterone is closely associated with lipid metabolism and known to affect body fat composition and muscle mass in males. However, the mechanisms by which testosterone acts on lipid metabolism are not yet fully understood, especially in teleosts. In this study, cyp17a1-/- zebrafish ( Danio rerio) exhibited excessive visceral adipose tissue (VAT), lipid content, and up-regulated expression and activity of hepatic de novo lipogenesis (DNL) enzymes. The assay for transposase accessible chromatin with sequencing (ATAC-seq) results demonstrated that chromatin accessibility of DNL genes was increased in cyp17a1-/- fish compared to cyp17a1+/+ male fish, including stearoyl-CoA desaturase ( scd) and fatty acid synthase ( fasn). Androgen response element (ARE) motifs in the androgen signaling pathway were significantly enriched in cyp17a1+/+ male fish but not in cyp17a1-/- fish. Both androgen receptor ( ar)-/- and wild-type (WT) zebrafish administered with Ar antagonist flutamide displayed excessive visceral adipose tissue, lipid content, and up-regulated expression and activity of hepatic de novo lipogenesis enzymes. The Ar agonist BMS-564929 reduced the content of VAT and lipid content, and down-regulated acetyl-CoA carboxylase a ( acaca), fasn, and scd expression. Mechanistically, the rescue effect of testosterone on cyp17a1-/- fish in terms of phenotypes was abolished when ar was additionally depleted. Collectively, these findings reveal that testosterone inhibits lipid deposition by down-regulating DNL genes via Ar in zebrafish, thus expanding our understanding of the relationship between testosterone and lipid metabolism in teleosts.

Trajectories of social isolation and loneliness and the risk of incident type 2 diabetes mellitus across genetic risk score.

AIM: This study aimed to investigate the association of social isolation, loneliness, and their trajectory with the risk of developing type 2 diabetes mellitus (T2DM) across genetic risk. METHODS: We included 439,337 participants (mean age 56.3 ± 8.1 years) enrolled in the UK Biobank study who were followed up until May 31, 2021. Social isolation and loneliness were self-reported and were further categorized into never, transient, incident, and persistent patterns. RESULTS: During a median follow-up of 12.7 years, 15,258 incident T2DM cases were documented. Social isolation (versus no social isolation: hazard ratio (HR) 95 % confidence interval (CI) 1.04 [1.00;1.09]) and loneliness (versus no loneliness: 1.26 [1.19;1.34]) were associated with an increased T2DM risk, independent of the genetic risk for T2DM. The interactions existed between social isolation and loneliness (Pinteraction < 0.05); the increased T2DM risk associated with social isolation was only significant among participants without loneliness. In the longitudinal analysis, only persistent social isolation (versus never social isolation: 1.22 [1.02;1.45]) was associated with an increased T2DM risk, whereas incident loneliness (versus never loneliness: 1.95 [1.40;2.71]) and persistent loneliness (2.00 [1.31;3.04]) were associated with higher T2DM risks. CONCLUSION: Social isolation and loneliness, especially their persistent pattern, were independently associated with an increased incident T2DM risk, irrespective of an individual's genetic risk. Loneliness modified the association between social isolation and incident T2DM.

Multi­omics approach to improve patient­tailored therapy using immune checkpoint blockade and cytokine­induced killer cell infusion in an elderly patient with lung cancer: A case report and literature review.

The 5-year survival rate of patients with advanced non-small cell lung cancer (NSCLC) remains low, despite recent advances in targeted therapy and immunotherapy. Therefore, there is a need to identify alternative strategies to improve treatment outcomes. Modern diagnostics can significantly facilitate the selection of treatment plans to improve patient outcomes. In the present study, multi-form diagnostic methodologies were adopted, including next-generation sequencing-based actionable gene sequencing, programmed death ligand 1 (PD-L1) immunohistochemistry, a circulating tumor cell (CTC) assay, flow cytometric analysis of lymphocyte subsets and computed tomography, to improve disease management in an 86-year-old female patient with relapsed metastatic NSCLC. High expression of PD-L1, elevated CTC tmutations, were observed. Based on these results, the patient was initially treated with the programmed death protein 1 blocking antibody sintilimab for two cycles, resulting in the stabilization of their condition, although the patient still exhibited severe pain and other symptoms, including fatigue, malaise, a loss of appetite and poor mental state. Informed by dynamic monitoring of the patient's response to treatment, the treatment plan was subsequently adjusted to a combination therapy with sintilimab and autologous cytokine-induced killer cell infusion, which eventually led to improved outcomes in both the management of the cancer and quality of life. In conclusion, multi-omics analysis may be used to establish patient-tailored therapies to improve clinical outcomes in hard-to-treat elderly patients with metastatic NSCLC.

Radiographic Imaging for the Diagnosis and Treatment of Patients with Skeletal Class III Malocclusion.

Skeletal Class III malocclusion is one type of dentofacial deformity that significantly affects patients' facial aesthetics and oral health. The orthodontic treatment of skeletal Class III malocclusion presents challenges due to uncertainties surrounding mandibular growth patterns and treatment outcomes. In recent years, disease-specific radiographic features have garnered interest from researchers in various fields including orthodontics, for their exceptional performance in enhancing diagnostic precision and treatment effect predictability. The aim of this narrative review is to provide an overview of the valuable radiographic features in the diagnosis and management of skeletal Class III malocclusion. Based on the existing literature, a series of analyses on lateral cephalograms have been concluded to identify the significant variables related to facial type classification, growth prediction, and decision-making for tooth extractions and orthognathic surgery in patients with skeletal Class III malocclusion. Furthermore, we summarize the parameters regarding the inter-maxillary relationship, as well as different anatomical structures including the maxilla, mandible, craniofacial base, and soft tissues from conventional and machine learning statistical models. Several distinct radiographic features for Class III malocclusion have also been preliminarily observed using cone beam computed tomography (CBCT) and magnetic resonance imaging (MRI).

Potential novel Colpodella spp. (phylum Apicomplexa) and high prevalence of Colpodella spp. in goat-attached Haemaphysalis longicornis ticks in Shandong province, China.

Tick-borne Apicomplexan parasites pose a significant threat to both public health and animal husbandry. Identifying potential pathogenic parasites and gathering their epidemiological data are essential for prospectively preventing and controlling infections. In the present study, genomic DNA of ticks collected from two goat flocks (Goatflock1 and Goatflock2) and one dog group (Doggroup) were extracted and the 18S rRNA gene of Babesia/Theileria/Colpodella spp. was amplified by PCR and sequenced. Phylogenetic analysis was conducted based on the obtained sequences. The differences in pathogen positive rates between ticks of different groups were statistically analyzed using the Chi-square or continuity-adjusted Chi-square test. As a result, two pathogenic Theileria (T.) luwenshuni genotypes, one novel pathogenic Colpodella sp. HLJ genotype, and two potential novel Colpodella spp. (referred to as Colpodella sp. struthionis and Colpodella sp. yiyuansis in this study) were identified in the Haemaphysalis (H.) longicornis ticks. Ticks of Goatflock2 had a significantly higher positive rate of Colpodella spp. than those from Goatflock1 (χ2=92.10; P = 8.2 × 10-22) and Doggroup (χ2=42.34; P = 7.7 × 10-11), and a significantly higher positive rate of T. luwenshuni than Doggroup (χ2=5.38; P = 0.02). However, the positive rates of T. luwenshuni between Goatflock1 and Goatflock2 were not significantly different (χ2=2.02; P = 0.16), and so as the positive rates of both pathogens between Goatflock1 and Doggroup groups (P > 0.05). For either Colpodella spp. or T. luwenshuni, no significant difference was found in prevalence between male and female ticks. These findings underscore the potential importance of Colpodella spp. in domestic animal-attached ticks, as our study revealed two novel Colpodella spp. and identified Colpodella spp. in H. longicornis for the first time. The study also sheds light on goats' potential roles in the transmission of Colpodella spp. to ticks and provides crucial epidemiological data of pathogenic Theileria and Colpodella. These data may help physicians, veterinarians, and public health officers prepare suitable detection and treatment methods and develop prevention and control strategies.

Time series models in prediction of severe fever with thrombocytopenia syndrome cases in Shandong province, China.

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging infectious disease caused by the SFTS virus (SFTSV). Predicting the incidence of this disease in advance is crucial for policymakers to develop prevention and control strategies. In this study, we utilized historical incidence data of SFTS (2013-2020) in Shandong Province, China to establish three univariate prediction models based on two time-series forecasting algorithms Autoregressive Integrated Moving Average (ARIMA) and Prophet, as well as a special type of recurrent neural network Long Short-Term Memory (LSTM) algorithm. We then evaluated and compared the performance of these models. All three models demonstrated good predictive capabilities for SFTS cases, with the predicted results closely aligning with the actual cases. Among the models, the LSTM model exhibited the best fitting and prediction performance. It achieved the lowest values for mean absolute error (MAE), mean square error (MSE), and root mean square error (RMSE). The number of SFTS cases in the subsequent 5 years in this area were also generated using this model. The LSTM model, being simple and practical, provides valuable information and data for assessing the potential risk of SFTS in advance. This information is crucial for the development of early warning systems and the formulation of effective prevention and control measures for SFTS.

Spatiotemporal heterogeneity and long-term impact of meteorological, environmental, and socio-economic factors on scrub typhus in China from 2006 to 2018.

BACKGROUND: Large-scale outbreaks of scrub typhus combined with its emergence in new areas as a vector-borne rickettsiosis highlight the ongoing neglect of this disease. This study aims to explore the long-term changes and regional leading factors of scrub typhus in China, with the goal of providing valuable insights for disease prevention and control. METHODS: This study utilized a Bayesian space-time hierarchical model (BSTHM) to examine the spatiotemporal heterogeneity of scrub typhus and analyze the relationship between environmental factors and scrub typhus in southern and northern China from 2006 to 2018. Additionally, a GeoDetector model was employed to assess the predominant influences of geographical and socioeconomic factors in both regions. RESULTS: Scrub typhus exhibits a seasonal pattern, typically occurring during the summer and autumn months (June to November), with a peak in October. Geographically, the high-risk regions, or hot spots, are concentrated in the south, while the low-risk regions, or cold spots, are located in the north. Moreover, the distribution of scrub typhus is influenced by environment and socio-economic factors. In the north and south, the dominant factors are the monthly normalized vegetation index (NDVI) and temperature. An increase in NDVI per interquartile range (IQR) leads to a 7.580% decrease in scrub typhus risk in northern China, and a 19.180% increase in the southern. Similarly, of 1 IQR increase in temperature reduces the risk of scrub typhus by 10.720% in the north but increases it by 15.800% in the south. In terms of geographical and socio-economic factors, illiteracy rate and altitude are the key determinants in the respective areas, with q-values of 0.844 and 0.882. CONCLUSIONS: These results indicated that appropriate climate, environment, and social conditions would increase the risk of scrub typhus. This study provided helpful suggestions and a basis for reasonably allocating resources and controlling the occurrence of scrub typhus.

Unveiling camouflaged and partially occluded colorectal polyps: Introducing CPSNet for accurate colon polyp segmentation.

BACKGROUND: Segmenting colorectal polyps presents a significant challenge due to the diverse variations in their size, shape, texture, and intricate backgrounds. Particularly demanding are the so-called "camouflaged" polyps, which are partially concealed by surrounding tissues or fluids, adding complexity to their detection. METHODS: We present CPSNet, an innovative model designed for camouflaged polyp segmentation. CPSNet incorporates three key modules: the Deep Multi-Scale-Feature Fusion Module, the Camouflaged Object Detection Module, and the Multi-Scale Feature Enhancement Module. These modules work collaboratively to improve the segmentation process, enhancing both robustness and accuracy. RESULTS: Our experiments confirm the effectiveness of CPSNet. When compared to state-of-the-art methods in colon polyp segmentation, CPSNet consistently outperforms the competition. Particularly noteworthy is its performance on the ETIS-LaribPolypDB dataset, where CPSNet achieved a remarkable 2.3% increase in the Dice coefficient compared to the Polyp-PVT model. CONCLUSION: In summary, CPSNet marks a significant advancement in the field of colorectal polyp segmentation. Its innovative approach, encompassing multi-scale feature fusion, camouflaged object detection, and feature enhancement, holds considerable promise for clinical applications.

The XPO1 inhibitor selinexor ameliorates bleomycin-induced pulmonary fibrosis in mice via GBP5/NLRP3 inflammasome signaling.

Pulmonary fibrosis is an irreversible and progressive lung disease with limited treatments available. Selinexor (Sel), an orally available, small-molecule, selective inhibitor of XPO1, exhibits notable antitumor, anti-inflammatory and antiviral activities. However, its potential role in treating pulmonary fibrosis is unknown. C57BL/6J mice were used to establish a pulmonary fibrosis model by intratracheal administration of bleomycin (BLM). Subsequently, Sel was administered intraperitoneally. Our data demonstrated that Sel administration ameliorated BLM-induced pulmonary fibrosis by increasing mouse body weights; reducing H&E staining, Masson staining scores, and shadows in mouse lung computed tomography (CT) images, decreasing the total cell and neutrophil counts in the lung and bronchoalveolar lavage fluid (BALF); and decreasing the levels of TGF-ß1. We next confirmed that Sel reduced the deposition of extracellular matrix (ECM) components in the lungs of BLM-induced pulmonary fibrosis mice. We showed that collagen I, alpha-smooth muscle actin (α-SMA), and hydroxyproline levels and the mRNA levels of Col1a1, Eln, Fn1, Ctgf, and Fgf2 were reduced. Mechanistically, tandem mass tags (TMT)- based quantitative proteomics analysis revealed a significant increase in GBP5 in the lungs of BLM mice but a decrease in that of BLM + Sel mice; this phenomenon was confirmed by western blotting and RT-qPCR. NLRP3 inflammasome signaling was significantly enriched in both the BLM group and BLM + Sel group based on GO and KEGG analyses of differentially expressed proteins between the groups. Furthermore, Sel reduced the expression of NLRP3, cleaved caspase 1, and ASC in vivo and in vitro, and decreased the levels of IL-1ß, IL-18, and IFN-r in lung tissue and BALF. SiRNA-GBP5 inhibited NLRP3 signaling in vitro, and overexpression of GBP5 inhibited the protective effect of Sel against BLM-induced cellular injury. Taken together, our findings indicate that Sel ameliorates BLM-induced pulmonary fibrosis by targeting GBP5 via NLRP3 inflammasome signaling. Thus, the XPO1 inhibitor - Sel might be a potential therapeutic agent for pulmonary fibrosis.

Identification and validation of SLCO4C1 as a biological marker in hepatocellular carcinoma based on anoikis classification features.

BACKGROUND: Hepatocellular carcinoma (HCC) exhibits a high degree of invasiveness and is closely associated with rapid disease progression. Multiple lines of evidence indicate a strong correlation between anoikis resistance and tumor progression, invasion, and metastasis. Nevertheless, the classification of anoikis in HCC and the investigation of novel biological target mechanisms in this context continue to pose challenges, requiring further exploration. METHODS: Combined with HCC samples from TCGA, GEO and ICGC databases, cluster analysis was conducted on anoikis genes, revealing novel patterns among different subtypes. Significant gene analysis of different gene subtypes was performed using WCGNA. The anoikis prognostic risk model was established by Lasso-Cox. Go, KEGG, and GSEA were applied to investigate pathway enrichment primarily observed in risk groups. We compared the disparities in immune infiltration, TMB, tumor microenvironment (TME), and drug sensitivity between the two risk groups. RT-qPCR and Western blotting were performed to validate the expression levels of SLCO4C1 in HCC. The biological functions of SLCO4C1 in HCC cells were assessed through various experiments, including CCK8 assay, colony formation assay, invasion migration assay, wound healing assay, and flow cytometry analysis. RESULTS: HCC was divided into 2 anoikis subtypes, and the subtypeB had a better prognosis. An anoikis prognostic model based on 12 (COPZ2, ACTG2, IFI27, SPP1, EPO, SLCO4C1, RAB26, STC2, RAC3, NQO1, MYCN, HSPA1B) risk genes is important for survival and prognosis. Significant differences were observed in immune cell infiltration, TME, and drug sensitivity analysis between the risk groups. SLCO4C1 was downregulated in HCC. SLCO4C1 downregulation promoted the proliferation, invasion, migration, and apoptosis of HCC cells. The tumor-suppressive role of SLCO4C1 in HCC has been confirmed. CONCLUSIONS: Our study presents a novel anoikis classification method for HCC that reveals the association between anoikis features and HCC. The anoikis feature is a critical biomarker bridging tumor cell death and tumor immunity. In this study, we provided the first evidence of SLCO4C1 functioning as a tumor suppressor in HCC.

Early detection of nasopharyngeal carcinoma: performance of a short contrast-free screening magnetic resonance imaging.

BACKGROUND: Although contrast-enhanced magnetic resonance imaging (MRI) detects early-stage nasopharyngeal carcinoma (NPC) not detected by endoscopic-guided biopsy (EGB), a short contrast-free screening MRI would be desirable for NPC screening programs. This study evaluated a screening MRI in a plasma Epstein-Barr virus (EBV)-DNA NPC screening program. METHODS: EBV-DNA-screen-positive patients underwent endoscopy, and endoscopy-positive patients underwent EGB. EGB was negative if the biopsy was negative or was not performed. Patients also underwent a screening MRI. Diagnostic performance was based on histologic confirmation of NPC in the initial study or during a follow-up period of at least 2 years. RESULTS: The study prospectively recruited 354 patients for MRI and endoscopy; 40/354 (11.3%) endoscopy-positive patients underwent EGB. Eighteen had NPC (5.1%), and 336 without NPC (94.9%) were followed up for a median of 44.8 months. MRI detected additional NPCs in 3/18 (16.7%) endoscopy-negative and 2/18 (11.1%) EGB-negative patients (stage I/II, n = 4; stage III, n = 1). None of the 24 EGB-negative patients who were MRI-negative had NPC. MRI missed NPC in 2/18 (11.1%), one of which was also endoscopy-negative. The sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of MRI, endoscopy, and EGB were 88.9%, 91.1%, 34.8%, 99.4%, and 91.0%; 77.8%, 92.3%, 35.0%, 98.7%, and 91.5%; and 66.7%, 92.3%, 31.6%, 98.1%, and 91.0%, respectively. CONCLUSION: A quick contrast-free screening MRI complements endoscopy in NPC screening programs. In EBV-screen-positive patients, MRI enables early detection of NPC that is endoscopically occult or negative on EGB and increases confidence that NPC has not been missed.

Chronic osteomyelitis risk is associated with NLRP3 gene rs10754558 polymorphism in a Chinese Han Population.

BACKGROUND: Single nucleotide polymorphisms (SNPs) in the nucleotide-binding domain leucine-rich repeat protein-3 (NLRP3) gene are reported to be linked to many inflammatory disorders. However, uncertainty persists over the associations between these SNPs and susceptibilities to chronic osteomyelitis (COM). This study aimed to investigate potential relationships between NLRP3 gene SNPs and the risks of developing COM in a Chinese Han cohort. METHODS: The four tag SNPs of the NLRP3 gene were genotyped in a total of 428 COM patients and 368 healthy controlsusing the SNapShot technique. The genotype distribution, mutant allele frequency, and the four genetic models (dominant, recessive, homozygous, and heterozygous) of the four SNPs were compared between the two groups. RESULTS: A significant association was found between rs10754558 polymorphism and the probability of COM occurence by the heterozygous model (P = 0.037, odds ratio [OR] = 1.541, 95% confidence interval [CI] = 1.025-2.319), indicating that rs10754558 may be associated with a higher risk of developing COM.In addition, possible relationship was found between rs7525979 polymorphism and the risk of COM development by the outcomes of homozygous (P = 0.073, OR = 0.453, 95% CI = 0.187-1.097) and recessive (P = 0.093, OR = 0.478, 95% CI = 0.198-1.151) models, though no statistical differences were obtained. CONCLUSIONS: Outcomes of the present study showed, for the first time, that rs10754558 polymorphism of the NLRP3 gene may increase the risk of COM development in this Chinese Han population, with genotype CG as a risk factor. Nonetheless, this conclusion requires verification from further studies with a larger sample size.

MicroRNA-18a regulates the Pyroptosis, Apoptosis, and Necroptosis (PANoptosis) of osteoblasts induced by tumor necrosis factor-α via hypoxia-inducible factor-1α.

BACKGROUND: Tumor necrosis factor-α (TNF-α) is involved in inflammatory responses and promotes cell death and the inhibition of osteogenic differentiation. MicroRNA (miRNA) plays a crucial role in the infected bone diseases, however, the biological role of miRNAs in inflammation-induced impaired osteogenic differentiation remains unclear. This study aimed to explore the role of miRNA-18a-5p (miR-18a) in regulating PANoptosis and osteogenic differentiation in an inflammatory environment via hypoxia-inducible factor-1α (HIF1-α). METHODS: The expression of miR-18a in MC3T3-E1 cells was analyzed using quantitative reverse transcription-polymerase chain reaction in an inflammatory environment induced by TNF-α. The expression of HIF1-α and NLRP3 in LV-miR-18a or sh-miR-18a cells was analyzed using western blotting. Fluorescence imaging for cell death, flow cytometry, and alkaline phosphatase activity analysis were used to analyze the role of miR-18a in TNF-α-induced PANoptosis and the inhibition of osteogenic differentiation. An animal model of infectious bone defect was established to validate the regulatory role of miR-18a in an inflammatory environment. RESULTS: The expression of miRNA-18a in the MC3T3-E1 cell line was significantly lower under TNF-α stimulation than in the normal environment. miR-18a significantly inhibited the expression of HIF1-α and NLRP3, and inhibition of HIF1-α expression further inhibited NLRP3 expression. Furthermore, inhibition of miR-18a expression promoted the TNF-α-induced PANoptosis and inhibition of osteogenic differentiation, whereas miR-18a overexpression and the inhibition of both HIF1-α and NLRP3 reduced the effects of TNF-α. These findings are consistent with those of the animal experiments. CONCLUSION: miRNA-18a negatively affects HIF1-α/NLRP3 expression, inhibits inflammation-induced PANoptosis, and impairs osteogenic differentiation. Thus, it is a potential therapeutic candidate for developing anti-inflammatory strategies for infected bone diseases.