2,5-Dihydroxyacetophenone attenuates acute kidney injury induced by intra-abdominal infection in rats.

AIMS: As one of the most serious complications of sepsis, acute kidney injury (AKI) is pathologically associated with excessive inflammation. 2,5-Dihydroxyacetophenone (DHAP) is isolated from Radix rehmanniae praeparata and exhibit potent anti-inflammatory property. This research aimed at determining the role of DHAP in sepsis-associated AKI (SA-AKI) and the underlying mechanism. METHODS: Plasma creatinine (Cre), blood urea nitrogen (BUN), tumour necrosis factor-α (TNF-α) and interleukin-1ß (IL-1ß) levels of SA-AKI patients were detected to evaluate their clinical characteristics. SA-AKI rat models were established by using caecum ligation puncture (CLP) surgery. CLP-induced rats were administered via oral gavage with 20 or 40 mg DHAP after 2 h of CLP surgery. Subsequently, survival rates, serum indexes, histopathological changes, inflammatory factors, renal function indexes and extracellular regulated protein kinases (ERK) and nuclear factor-κB (NF-κB) signalling pathways were detected. RESULTS: SA-AKI patients exhibited markedly higher levels of plasma Cre, BUN, TNF-α and IL-1ß than healthy people. Compared with sham rats, CLP-induced septic rats showed significantly decreased survival rate, increased serum lactate dehydrogenase activity and serum lactate level, obvious renal histopathological injury, upregulated TNF-α, IL-1ß and TGF-ß1 levels, elevated serum creatinine, BUN and serum cystatin C concentrations, serum neutrophil gelatinase-associated lipocalin and kidney injury molecule-1 levels and reduced renal artery blood flow. All the above CLP-induced changes in septic rats were mitigated after DHAP administration. Additionally, CLP-induced elevation in phosphorylated-ERK1/2 and nuclear NF-κB p65 protein levels was inhibited by DHAP treatment. CONCLUSION: DHAP hinders SA-AKI progression in rat models by inhibiting ERK and NF-κB signalling pathways.

Predicting the 28-day prognosis of acute-on-chronic liver failure patients based on machine learning.

BACKGROUND: We aimed to establish a prognostic predictive model based on machine learning (ML) methods to predict the 28-day mortality of acute-on-chronic liver failure (ACLF) patients, and to evaluate treatment effectiveness. METHODS: ACLF patients from six tertiary hospitals were included for analysis. Features for ML models' development were selected by LASSO regression. Models' performance was evaluated by area under the curve (AUC) and accuracy. Shapley additive explanation was used to explain the ML model. RESULTS: Of the 736 included patients, 587 were assigned to a training set and 149 to an external validation set. Features selected included age, hepatic encephalopathy, total bilirubin, PTA, and creatinine. The eXtreme Gradient Boosting (XGB) model outperformed other ML models in the prognostic prediction of ACLF patients, with the highest AUC and accuracy. Delong's test demonstrated that the XGB model outperformed Child-Pugh score, MELD score, CLIF-SOFA, CLIF-C OF, and CLIF-C ACLF. Sequential assessments at baseline, day 3, day 7, and day 14 improved the predictive performance of the XGB-ML model and can help clinicians evaluate the effectiveness of medical treatment. CONCLUSIONS: We established an XGB-ML model to predict the 28-day mortality of ACLF patients as well as to evaluate the treatment effectiveness.

Effects of dietary salidroside on intestinal health, immune parameters and intestinal microbiota in largemouth bass (Micropterus salmoides).

The largemouth bass has become one of the economically fish in China, according to the latest China Fishery Statistical Yearbook. The farming scale is constantly increasing. Salidroside has been found in past studies to have oxidative stress reducing and immune boosting properties. In this study, the addition of six different levels of salidroside supplements were 0、40、80、120、160 and 200 mg/kg. A 56-day feeding trial was conducted to investigate the effects of salidroside on the intestinal health, immune parameters and intestinal microbiota composition of largemouth bass. Dietary addition of salidroside significantly affected the Keap-1ß/Nrf-2 pathway as well as significantly increased antioxidant enzyme activities resulting in a significant increase in antioxidant capacity of largemouth bass. Dietary SLR significantly reduced feed coefficients. The genes related to tight junction proteins (Occludin, ZO-1, Claudin-4, Claudin-5) were found to be significantly upregulated in the diet supplemented with salidroside, indicating that salidroside can improve the intestinal barrier function (p < 0.05). The dietary administration of salidroside was found to significantly reduce the transcription levels of intestinal tumor necrosis factor-α (TNF-α) and interleukin-1ß (IL-1ß) (p < 0.05). Furthermore, salidroside was observed to reduce the transcription levels of intestinal apoptosis factor Bcl-2 associated death promoter (BAD) and recombinant Tumor Protein p53 (P53) (p < 0.05). Concomitantly, the beneficial bacteria, Fusobacteriota and Cetobacterium, was significantly increased in the SLR12 group, while that of pathogenic bacteria, Proteobacteria, was significantly decreased (p < 0.05). In conclusion, the medium-sized largemouth bass optimal dosage of salidroside in the diet is 120mg/kg-1.

A strategy to reconstitute immunity without GVHD via adoptive allogeneic Tscm therapy.

Introduction: Adoption of allogeneic T cells directly supplements the number of T cells and rapidly induces T-cell immunity, which has good efficacy for treating some tumors and immunodeficiency diseases. However, poor adoptive T-cell engraftment and graft-versus-host disease (GVHD) limit the application of these methods. Alloreactive T-cell clones were eliminated from the donor T-cell repertoire, and the remaining T-cell clones were prepared as Tscm for T-cell adoptive treatment to reconstruct recipient T-cell immunity without GVHD. Methods: The subjects in this study included three different strains of mice. Lymphocytes from mice (C57BL/6) were used as the donor T-cell repertoire, from which the Tscm allo-reactive T cell clone was depleted (ATD-Tscm). This was confirmed by showing that the Tscm was not responsive to the alloantigen of the recipient (BALB/c). To prepare ATD-Tscm cells, we used recipient lymphocytes as a simulator, and coculture of mouse and recipient lymphocytes was carried out for 7 days. Sorting of non-proliferative cells ensured that the prepared Tscm cells were nonresponsive. The sorted lymphocytes underwent further expansion by treatment with TWS119 and cytokines for an additional 10 days, after which the number of ATD-Tscm cells increased. The prepared Tscm cells were transferred into recipient mice to observe immune reconstitution and GVHD incidence. Results: Our protocol began with the use of 1×107 donor lymphocytes and resulted in 1 ×107 ATD-Tscm cells after 17 days of preparation. The prepared ATD-Tscm cells exhibited a nonresponse upon restimulation of the recipient lymphocytes. Importantly, the prepared ATD-Tscm cells were able to bind long and reconstitute other T-cell subsets in vivo, effectively recognizing and answering the "foreign" antigen without causing GVHD after they were transferred into the recipients. Discussion: Our strategy was succeeded to prepare ATD-Tscm cells from the donor T-cell repertoire. The prepared ATD-Tscm cells were able to reconstitute the immune system and prevent GVHD after transferred to the recipients. This study provides a good reference for generating ATD-Tscm for T-cell adoptive immunotherapy.

Nomogram of magnetic resonance imaging (MRI) histogram analysis to predict telomerase reverse transcriptase promoter mutation status in glioblastoma.

Background: Telomerase reverse transcriptase promoter (pTERT) status is a strong biomarker to diagnose and predict the prognosis of glioblastoma (GBM). In this study, we explored the predictive value of preoperative magnetic resonance imaging (MRI) histogram analysis in the form of nomogram for evaluating pTERT mutation status in GBM. Methods: The clinical and imaging data of 181 patients with GBM at our hospital between November 2018 and April 2023 were retrospectively assessed. We used the molecular sequencing results to classify the datasets into pTERT mutations (C228T and C250T) and pTERT-wildtype groups. FireVoxel software was used to extract preoperative T1-weighted contrast-enhanced (T1C) histogram parameters of GBM patients. The T1C histogram parameters were compared between groups. Univariate and multivariate logistic regression analyses were used to construct the nomogram, and the predictive efficacy of model was evaluated using calibration and decision curves. Receiver operating characteristic curve was used to assess model performance. Results: Patient age and percentage of unenhanced tumor area showed statistically significant differences between the pTERT mutation and pTERT-wildtype groups (P<0.001). Among the T1C histogram features, the maximum, standard deviation (SD), variance, coefficient of variation (CV), skewness, 5th, 10th, 25th, 95th and 99th percentiles were statistically significantly different between groups (P=0.000-0.040). Multivariate logistic regression analysis showed that age, percentage of unenhanced tumor area, SD and CV were independent risk factors for predicting pTERT mutation status in GBM patients. The logistic regression model based on these four features showed a better sample predictive performance, and the area under the curve (AUC) [95% confidence interval (CI)], accuracy, sensitivity, specificity were 0.842 (0.767-0.917), 0.796, 0.820, and 0.729, respectively. There were no significant differences in the T1C histogram parameters between the C228T and C250T groups (P=0.055-0.854). Conclusions: T1C histogram parameters can be used to evaluate pTERT mutations status in GBM. A nomogram based on conventional MRI features and T1C histogram parameters is a reliable tool for the pTERT mutation status, allowing for non-invasive radiological prediction before surgery.

Emission characteristics of lead and particulate matter from lead and zinc smelters in China.

Understanding the emission characteristics of particulate matter and associated heavy metals is essential for assessing their environmental and health impacts post-emission, as well as for identifying potential control technologies for the sources. Here, a field test was conducted at two advanced smelting plants equipped with comprehensive air pollution control devices. The particles emitted from different stages of lead and zinc smelting exhibited bi-modal size distributions, with peaks observed in PM0.1-1.0 and PM2.5-10, respectively. Particulate-bound Pb was identified as the predominant Pb species in the flue gas, primarily originating from ore crushing. Consequently, over 80 % of Pb was emitted in the form of coarse particles, a marked contrast to coal-fired power plants where Pb concentrated on fine particles. High efficiencies in Pb removal were achieved by dust collectors, flue gas purification systems, and acid plants with desulfurization systems, resulting in overall Pb emission factors in lead and zinc smelting were only 89.3 and 2.60 g t-1 (of metal production), respectively. Importantly, the contribution of gas-phase Pb, which accounts for approximately 16.6 % of total emissions, must not be neglected in future emission monitoring and control efforts.

High-Sensitive Uncooled Mid-Wave Infrared Detector Based on TiS3 Nanoribbon.

High-sensitive uncooled mid-wave infrared (MWIR) photodetection with fast speed is highly desired for biomedical imaging, optical communication, and night vision technology. Low-dimensional materials with low dark current and broadband photoresponse hold great promise for use in MWIR detection. Here, this study reports a high-performance MWIR photodetector based on a titanium trisulfide (TiS3) nanoribbon. This device demonstrates an ultra-broadband photoresponse ranging from the visible spectrum to the MWIR spectrum (405-4275 nm). In the MWIR spectral range, the photodetector achieves competitive high photoresponsivity (R) of 21.1 A W-1, and an impressive specific detectivity (D*) of 5.9 × 1010 cmHz1/2 W-1 in ambient air. Remarkably, the photoresponse speed in the MWIR with τr = 1.3 ms and τd = 1.5 ms is realized which is much faster than the thermal time constant of 15 ms. These findings pave the way for highly sensitive, room-temperature MWIR photodetectors with exceptionally fast response speed.

Cross-Anatomy Transfer Learning via Shape- Aware Adaptive Fine-Tuning for 3D Vessel Segmentation.

Deep learning methods have recently achieved remarkable performance in vessel segmentation applications, yet require numerous labor-intensive labeled data. To alleviate the requirement of manual annotation, transfer learning methods can potentially be used to acquire the related knowledge of tubular structures from public large-scale labeled vessel datasets for target vessel segmentation in other anatomic sites of the human body. However, the cross-anatomy domain shift is a challenging task due to the formidable discrepancy among various vessel structures in different anatomies, resulting in the limited performance of transfer learning. Therefore, we propose a cross-anatomy transfer learning framework for 3D vessel segmentation, which first generates a pre-trained model on a public hepatic vessel dataset and then adaptively fine-tunes our target segmentation network initialized from the model for segmentation of other anatomic vessels. In the framework, the adaptive fine-tuning strategy is presented to dynamically decide on the frozen or fine-tuned filters of the target network for each input sample with a proxy network. Moreover, we develop a Gaussian-based signed distance map that explicitly encodes vessel-specific shape context. The prediction of the map is added as an auxiliary task in the segmentation network to capture geometry-aware knowledge in the fine-tuning. We demonstrate the effectiveness of our method through extensive experiments on two small-scale datasets of coronary artery and brain vessel. The results indicate the proposed method effectively overcomes the discrepancy of cross-anatomy domain shift to achieve accurate vessel segmentation for these two datasets.

A bibliometric analysis of immune-related adverse events in cancer patients and a meta-analysis of immune-related adverse events in patients with hepatocellular carcinoma.

Background and Objectives: Immunotherapy has become the standard treatment for hepatocellular carcinoma (HCC), but it carries a risk of immune-related adverse events (irAEs) that can be life-threatening. This study employs bibliometric analysis to understand global scientific research on irAEs in cancer, focusing on characteristics and areas of interest. Additionally, a meta-analysis provides a comprehensive overview of irAEs in HCC patients receiving immune checkpoint inhibitor (ICI)-based therapies. Methods: We conducted a thorough search of Web of Science Core Collection (WoSCC) publications from 1999 to 2022. R and VOSviewer software were used for analysis. A meta-analysis was performed using data from PubMed, Embase, and the Cochrane Library databases up to March 22, 2022. Trials with HCC patients reporting irAE incidence were included. Quality assessment followed Cochrane risk of bias, Newcastle-Ottawa Scale (NOS), and Methodological Index for Non-Randomized Studies (MINORS). We used random-effects or fixed-effects models based on I2 values. Primary outcomes included any-grade irAEs and grade ≥ 3 irAEs. This review and meta-analysis are registered in PROSPERO as CRD42022318885. Results: In bibliometric analysis, we included 2946 papers, showing a consistent rise in annual publications on irAEs in cancer research. Frequent keywords were "nivolumab", "immune checkpoint inhibitor", and "immune-related adverse event". "Hepatocellular carcinoma" emerged as a prominent research focus linked to irAEs. We conducted a comprehensive meta-analysis on irAE incidence in HCC patients, including 29 studies. The overall incidence of any-grade irAEs was 61.0% (95% CI 38.5%-81.3%), and grade ≥ 3 irAEs was 13.2% (95% CI 7.9%-19.6%). Treatment-related mortality occurred in 3.1% (95% CI 0.8%-6.3%), with treatment discontinuation at 10.7% (95% CI 6.3%-16.0%). Reactive cutaneous capillary endothelial proliferation (RCCEP) was the most common any-grade irAE, while elevated aspartate aminotransferase (AST) was the most common grade ≥ 3 irAE. Treatment strategies were independently associated with specific irAEs, as indicated by multivariable analysis. Conclusion: This study provides valuable insights into the current research landscape of irAEs in cancer and ofers a comprehensive overview of irAEs in HCC patients undergoing ICI-based therapy. The relatively high incidence of irAEs and their association with treatment strategies emphasize the need for careful management by clinicians when treating HCC patients. These findings offer significant guidance for optimizing care and treatment for HCC patients.

Liensinine inhibits IL-1ß-stimulated inflammatory response in chondrocytes and attenuates papain-induced osteoarthritis in rats.

Osteoarthritis (OA) is a joint disease caused by inflammation of cartilage and synovial tissue. Suppressing the process of inflammatory reaction and the generation of oxidative stress is an effective strategy to alleviate the progression of OA. Liensinine is one of the main components of lotus seeds, which has anti-hypertensive and anti-arrhythmia activities. In this study, we aimed to determine the anti-inflammatory effect of liensinine in an OA. Here, we found that liensinine significantly inhibited the inflammatory response of SW1353 cells and primary chondrocytes by inhibiting the release of inflammatory cytokines and oxidative stress. Moreover, we showed that liensinine was able to inhibit the activation of the NF-κB signaling pathway in IL-1ß-induced SW1353 cells. Lastly, we found that liensinine significantly ameliorated cartilage damage and inflammatory response in papain-induced rats. Our study demonstrated a significant protective effect of liensinine against OA, which might be by inhibiting the activation of the NF-κB signaling pathway, and provide a new insight for the treatment of OA using liensinine.

Correlation of bilateral M1 hand area excitability and overall functional recovery after spinal cord injury: protocol for a prospective cohort study.

BACKGROUND: After spinal cord injury (SCI), a large number of survivors suffer from severe motor dysfunction (MD). Although the injury site is in the spinal cord, excitability significantly decreases in the primary motor cortex (M1), especially in the lower extremity (LE) area. Unfortunately, M1 LE area-targeted repetitive transcranial magnetic stimulation (rTMS) has not achieved significant motor improvement in individuals with SCI. A recent study reported that the M1 hand area in individuals with SCl contains a compositional code (the movement-coding component of neural activity) that links matching movements from the upper extremities (UE) and the LE. However, the correlation between bilateral M1 hand area excitability and overall functional recovery is unknown. OBJECTIVE: To clarify the changes in the excitability of the bilateral M1 hand area after SCI and its correlation with motor recovery, we aim to specify the therapeutic parameters of rTMS for SCI motor rehabilitation. METHODS: This study is a 12-month prospective cohort study. The neurophysiological and overall functional status of the participants will be assessed. The primary outcomes included single-pulse and paired-pulse TMS. The second outcome included functional near-infrared spectroscopy (fNIRS) measurements. Overall functional status included total motor score, modified Ashworth scale score, ASIA Impairment Scale grade, spinal cord independence measure and modified Barthel index. The data will be recorded for individuals with SCI at disease durations of 1 month, 2 months, 4 months, 6 months and 12 months. The matched healthy controls will be measured during the same period of time after recruitment. DISCUSSION: The present study is the first to analyze the role of bilateral M1 hand area excitability changes in the evaluation and prediction of overall functional recovery (including motor function and activities of daily living) after SCI, which will further expand the traditional theory of the predominant role of M1, optimize the current rTMS treatment, and explore the brain-computer interface design for individuals with SCI. TRIAL REGISTRATION NUMBER: ChiCTR2300068831.

Integrated multi-omics analysis and machine learning to refine molecular subtypes, prognosis, and immunotherapy in lung adenocarcinoma.

Lung adenocarcinoma (LUAD) has a malignant characteristic that is highly aggressive and prone to metastasis. There is still a lack of suitable biomarkers to facilitate the refinement of precision-based therapeutic regimens. We used a combination of 10 known clustering algorithms and the omics data from 4 dimensions to identify high-resolution molecular subtypes of LUAD. Subsequently, consensus machine learning-related prognostic signature (CMRS) was developed based on subtypes related genes and an integrated program framework containing 10 machine learning algorithms. The efficiency of CMRS was analyzed from the perspectives of tumor microenvironment, genomic landscape, immunotherapy, drug sensitivity, and single-cell analysis. In terms of results, through multi-omics clustering, we identified 2 comprehensive omics subtypes (CSs) in which CS1 patients had worse survival outcomes, higher aggressiveness, mRNAsi and mutation frequency. Subsequently, we developed CMRS based on 13 key genes up-regulated in CS1. The prognostic predictive efficiency of CMRS was superior to most established LUAD prognostic signatures. CMRS demonstrated a strong correlation with tumor microenvironmental feature variants and genomic instability generation. Regarding clinical performance, patients in the high CMRS group were more likely to benefit from immunotherapy, whereas low CMRS were more likely to benefit from chemotherapy and targeted drug therapy. In addition, we evaluated that drugs such as neratinib, oligomycin A, and others may be candidates for patients in the high CMRS group. Single-cell analysis revealed that CMRS-related genes were mainly expressed in epithelial cells. The novel molecular subtypes identified in this study based on multi-omics data could provide new insights into the stratified treatment of LUAD, while the development of CMRS could serve as a candidate indicator of the degree of benefit of precision therapy and immunotherapy for LUAD.

3D Nanoprinting of Heterogeneous Metal Oxides with High Shape Fidelity.

3D nanoprinting can significantly enhance the performance of sensors, batteries, optoelectronic/microelectronic devices, etc. However, current 3D nanoprinting methods for metal oxides are suffering from three key issues including limited material applicability, serious shape distortion, and the difficulty of heterogeneous integration. This paper discovers a mechanism in which imidazole and acrylic acid synergistically coordinate with metal ions in water. Using the mechanism, this work develops a series of metal ion synergistic coordination water-soluble (MISCWS) resins for 3D nanoprinting of various metal oxides, including MnO2, Cr2O3, Co3O4, and ZnO, as well as heterogeneous structures of MnO2/NiO, Cr2O3/Al2O3, and ZnO/MgO. Besides, the synergistic coordination effect results in a 2.54-fold increase in inorganic mass fraction within the polymer, compared with previous works, which effectively mitigates the shape distortion of metal oxide microstructures. Based on this method, this work also demonstrates a 3D ZnO microsensor with a high sensitivity (1.113 million at 200 ppm NO2), surpassing the conventional 2D ZnO sensors by tenfold. The method yields high-fidelity 3D structures of heterogeneous metal oxides with nanoscale resolution, paving the way for applications such as sensing, micro-optics, energy storage, and microsystems.

Association between Pericoronary Fat Attenuation Index Values and Plaque Composition Volume Fraction Measured by Coronary Computed Tomography Angiography.

RATIONALE AND OBJECTIVES: The pericoronary fat attenuation index (FAI) values around plaques may reveal the relationship between periplaque vascular inflammation and different plaque component volume fractions. We aimed to evaluate the potential associations between periplaque FAI values and plaque component volume fractions. MATERIALS AND METHODS: 496 patients (1078 lesions) with coronary artery disease, who underwent computed tomography angiography (CCTA) between September 2022 and August 2023, were analyzed retrospectively. Each lesion was characterized and the plaque component volume fractions and periplaque FAI values were measured. Multiple linear regression, weighted quantile sum (WQS) regression, and quantile g-computation (Qgcomp) were used to explore the relationship between plaque component volume fractions and the risk of elevated periplaque FAI values. RESULTS: After adjusting for clinical characteristics, multiple linear regression identified that lipid components volume fraction (ß = 0.162, P < 0.001) were independent risk factors for elevated periplaque FAI values whereas calcified components volume fraction (ß = -0.066, P = 0.025) were independent protective factors. The WQS regression models indicated an increase in the overall confounding effect of the adjusted lipid indices and plaque composition volume fraction on the risk of elevated periplaque FAI values (P = 0.004). Qgcomp analysis indicated lipid component volume fraction and calcified component volume fraction was positively and negatively correlated with elevated plaque FAI values, respectively (all P < 0.05). CONCLUSIONS: Periplaque FAI values quantified by CCTA were strongly correlated with lipid and calcification component volume fractions.

System analysis based on Anoikis-related genes identifies MAPK1 as a novel therapy target for osteosarcoma with neoadjuvant chemotherapy.

BACKGROUND: Osteosarcoma (OS) is the most common bone malignant tumor in children, and its prognosis is often poor. Anoikis is a unique mode of cell death.However, the effects of Anoikis in OS remain unexplored. METHOD: Differential analysis of Anoikis-related genes was performed based on the metastatic and non-metastatic groups. Then LASSO logistic regression and SVM-RFE algorithms were applied to screen out the characteristic genes. Later, Univariate and multivariate Cox regression was conducted to identify prognostic genes and further develop the Anoikis-based risk score. In addition, correlation analysis was performed to analyze the relationship between tumor microenvironment, drug sensitivity, and prognostic models. RESULTS: We established novel Anoikis-related subgroups and developed a prognostic model based on three Anoikis-related genes (MAPK1, MYC, and EDIL3). The survival and ROC analysis results showed that the prognostic model was reliable. Besides, the results of single-cell sequencing analysis suggested that the three prognostic genes were closely related to immune cell infiltration. Subsequently, aberrant expression of two prognostic genes was identified in osteosarcoma cells. Nilotinib can promote the apoptosis of osteosarcoma cells and down-regulate the expression of MAPK1. CONCLUSIONS: We developed a novel Anoikis-related risk score model, which can assist clinicians in evaluating the prognosis of osteosarcoma patients in clinical practice. Analysis of the tumor immune microenvironment and chemotherapeutic drug sensitivity can provide necessary insights into subsequent mechanisms. MAPK1 may be a valuable therapeutic target for neoadjuvant chemotherapy in osteosarcoma.

Prediction of O(6)-methylguanine-DNA methyltransferase promoter methylation status in IDH-wildtype glioblastoma using MRI histogram analysis.

To evaluate the utility of magnetic resonance imaging (MRI) histogram parameters in predicting O(6)-methylguanine-DNA methyltransferase promoter (pMGMT) methylation status in IDH-wildtype glioblastoma (GBM). From November 2021 to July 2023, forty-six IDH-wildtype GBM patients with known pMGMT methylation status (25 unmethylated and 21 methylated) were enrolled in this retrospective study. Conventional MRI signs (including location, across the midline, margin, necrosis/cystic changes, hemorrhage, and enhancement pattern) were assessed and recorded. Histogram parameters were extracted and calculated by Firevoxel software based on contrast-enhanced T1-weighted images (CET1). Differences and diagnostic performance of conventional MRI signs and histogram parameters between the pMGMT-unmethylated and pMGMT-methylated groups were analyzed and compared. No differences were observed in the conventional MRI signs between pMGMT-unmethylated and pMGMT-methylated groups (all p > 0.05). Compared with the pMGMT-methylated group, pMGMT-unmethylated showed a higher minimum, mean, Perc.01, Perc.05, Perc.10, Perc.25, Perc.50, and coefficient of variation (CV) (all p < 0.05). Among all significant CET1 histogram parameters, minimum achieved the best distinguishing performance, with an area under the curve of 0.836. CET1 histogram parameters could provide additional value in predicting pMGMT methylation status in patients with IDH-wildtype GBM, with minimum being the most promising parameter.

Exploring the impact of osteoprotegerin on osteoclast and precursor fusion: Mechanisms and modulation by ATP.

Osteoclast (OC) differentiation, vital for bone resorption, depends on osteoclast and precursor fusion. Osteoprotegerin (OPG) inhibits osteoclast differentiation. OPG's influence on fusion and mechanisms is unclear. Osteoclasts and precursors were treated with OPG alone or with ATP. OPG significantly reduced OC number, area and motility and ATP mitigated OPG's inhibition. However, OPG hardly affected the motility of precusors. OPG downregulated fusion-related molecules (CD44, CD47, DC-STAMP, ATP6V0D2) in osteoclasts, reducing only CD47 in precursors. OPG reduced Connexin43 phosphorylated forms (P1 and P2) in osteoclasts, affecting only P2 in precursors. OPG disrupted subcellular localization of CD44, CD47, DC-STAMP, ATP6V0D2, and Connexin43 in both cell types. Findings underscore OPG's multifaceted impact, inhibiting multinucleated osteoclast and mononuclear precursor fusion through distinct molecular mechanisms. Notably, ATP mitigates OPG's inhibitory effect, suggesting a potential regulatory role for the ATP signaling pathway. This study enhances understanding of intricate processes in osteoclast differentiation and fusion, offering insights into potential therapeutic targets for abnormal bone metabolism.

18ß-glycyrrhetinic acid ameliorates bleomycin-induced idiopathic pulmonary fibrosis via inhibiting TGF-ß1/JAK2/STAT3 signaling axis.

Idiopathic pulmonary fibrosis (IPF) is a debilitating and progressive lung disease with an unknown cause that has few treatment options. 18ß-Glycyrrhetinic acid (18ß-GA) is the main bioactive component in licorice, exhibiting anti-inflammatory and antioxidant effects, while also holding certain application value in the metabolism and regulation of steroids. In this study, we demonstrated that 18ß-GA effectively alleviates bleomycin (BLM)-induced IPF by inhibiting the TGF-ß1/JAK2/STAT3 signaling axis. In vivo experiments demonstrate that 18ß-GA significantly attenuates pulmonary fibrosis progression by reducing lung inflammation, improving lung function, and decreasing collagen deposition. In vitro experiments reveal that 18ß-GA inhibits the activation and migration of TGF-ß1-induced fibroblasts. Furthermore, it regulates the expression of vimentin, N-cadherin and E-cadherin proteins, thereby inhibiting TGF-ß1-induced epithelial-mesenchymal transition (EMT) in lung alveolar epithelial cells. Mechanistically, 18ß-GA ameliorates pulmonary fibrosis by modulating the TGF-ß1/JAK2/STAT3 signaling pathway in activated fibroblasts. Taken together, our findings demonstrate the potential and underlying mechanisms of 18ß-GA in ameliorating IPF, emphasizing its potential as a novel therapeutic drug for the treatment of this devastating disease.

KIF2C as a potential therapeutic target: insights from lung adenocarcinoma subtype classification and functional experiments.

Objective: this study evaluates the prognostic relevance of gene subtypes and the role of kinesin family member 2C (KIF2C) in lung cancer progression. Methods: high-expression genes linked to overall survival (OS) and progression-free interval (PFI) were selected from the TCGA-LUAD dataset. Consensus clustering analysis categorized lung adenocarcinoma (LUAD) patients into two subtypes, C1 and C2, which were compared using clinical, drug sensitivity, and immunotherapy analyses. A random forest algorithm pinpointed KIF2C as a prognostic hub gene, and its functional impact was assessed through various assays and in vivo experiments. Results: The study identified 163 key genes and distinguished two LUAD subtypes with differing OS, PFI, pathological stages, drug sensitivity, and immunotherapy response. KIF2C, highly expressed in the C2 subtype, was associated with poor prognosis, promoting cancer cell proliferation, migration, invasion, and epithelial-mesenchymal transition (EMT), with knockdown reducing tumor growth in mice. Conclusion: The research delineates distinct LUAD subtypes with significant clinical implications and highlights KIF2C as a potential therapeutic target for personalized treatment in LUAD.

MRI features and tumor-infiltrating CD8 + T cells-based nomogram for predicting meningioma recurrence risk.

OBJECTIVE: This study was based on MRI features and number of tumor-infiltrating CD8 + T cells in post-operative pathology, in predicting meningioma recurrence risk. METHODS: Clinical, pathological, and imaging data of 102 patients with surgically and pathologically confirmed meningiomas were retrospectively analyzed. Patients were divided into recurrence and non-recurrence groups based on follow-up. Tumor-infiltrating CD8 + T cells in tissue samples were quantitatively assessed with immunohistochemical staining. Apparent diffusion coefficient (ADC) histogram parameters from preoperative MRI were quantified in MaZda. Considering the high correlation between ADC histogram parameters, we only chose ADC histogram parameter that had the best predictive efficacy for COX regression analysis further. A visual nomogram was then constructed and the recurrence probability at 1- and 2-years was determined. Finally, subgroup analysis was performed with the nomogram. RESULTS: The risk factors for meningioma recurrence were ADCp1 (hazard ratio [HR] = 0.961, 95% confidence interval [95% CI]: 0.937 ~ 0.986, p = 0.002) and CD8 + T cells (HR = 0.026, 95%CI: 0.001 ~ 0.609, p = 0.023). The resultant nomogram had AUC values of 0.779 and 0.784 for 1- and 2-years predicted recurrence rates, respectively. The survival analysis revealed that patients with low CD8 + T cells counts or ADCp1 had higher recurrence rates than those with high CD8 + T cells counts or ADCp1. Subgroup analysis revealed that the AUC of nomogram for predicting 1-year and 2-year recurrence of WHO grade 1 and WHO grade 2 meningiomas was 0.872 (0.652) and 0.828 (0.751), respectively. CONCLUSIONS: Preoperative ADC histogram parameters and tumor-infiltrating CD8 + T cells may be potential biomarkers in predicting meningioma recurrence risk. CLINICAL RELEVANCE STATEMENT: The findings will improve prognostic accuracy for patients with meningioma and potentially allow for targeted treatment of individuals who have the recurrent form.