Comments and illustrations of the WFUMB CEUS liver guidelines: rare benign hematological focal liver lesions (hepatic extramedullary hematopoiesis, Hemophagocytic lymphohistiocytosis, reactive lymphoid hyperplasia).

The manifestation of benign hematological infiltration in the liver is a challenge due to their rare occurrence and therefore, limited awareness and the general need for biopsy and histological confirmation. Owing to the rarity of these lesions, there are limited data concerning their appearance on ultrasound and, specifically, contrast-enhanced ultrasound. In a series of papers, we have compiled the US and CEUS characteristics of rare FLL, where there are few reports and images available, in order to build up a library of these cases. This paper describes the US and CEUS features of benign hematological FLL which include hepatic extramedullary hematopoiesis (EMH), hemophagocytic lymphohistiocytosis (HLH) and reactive lymphoid hyperplasia (RLH). Although these lesions occur rarely in the liver, their correct identification is imperative for appropriate patient`s management.

Nonalternating π-System Mediated Spin Coupling in Azulene Nitronyl Nitroxide Diradicals.

To explore the distinctions in spin coupling between the molecular bridges of alternating and nonalternating π-systems, we synthesized a pair of isoelectronic compounds, namely, 2,6-Na-NN and 2,6-Az-NN, by utilizing naphthalene and azulene (naphthalene = Na and azulene = Az) as the bridges, respectively. Moreover, we conducted assessments to predict the coupling paths for nonalternating azulene. Variable-temperature EPR (VT-EPR) and SQUID results consistently reveal that both 2,6-Na-NN and 2,6-Az-NN exhibit antiferromagnetic coupling interactions, with coupling constants of J(2,6-Na-NN) = -22.3 cm-1 and J(2,6-Az-NN) = -30.1 cm-1, respectively. Density functional theory computations support these discoveries by revealing negative coupling constants (J < 0) and the spin densities population of the diradicals are observed to delocalize into the molecular bridges. This work suggests the most suitable coupling path for 2,6-Az-NN. In addition, we have investigated the potential spatial resistance of the diradicals in conjunction with single-crystal data. Theoretical calculations underestimating the torsion angle of the diradicals and overestimating the value of the magnetic coupling provide an explanation for this phenomenon. The final experimental results and theoretical calculations show that the 2,6-Az-NN coupling path prefers short paths.

Dynamic 3D Point Cloud Sequences as 2D Videos.

Dynamic 3D point cloud sequences serve as one of the most common and practical representation modalities of dynamic real-world environments. However, their unstructured nature in both spatial and temporal domains poses significant challenges to effective and efficient processing. Existing deep point cloud sequence modeling approaches imitate the mature 2D video learning mechanisms by developing complex spatio-temporal point neighbor grouping and feature aggregation schemes, often resulting in methods lacking effectiveness, efficiency, and expressive power. In this paper, we propose a novel generic representation called Structured Point Cloud Videos (SPCVs). Intuitively, by leveraging the fact that 3D geometric shapes are essentially 2D manifolds, SPCV re-organizes a point cloud sequence as a 2D video with spatial smoothness and temporal consistency, where the pixel values correspond to the 3D coordinates of points. The structured nature of our SPCV representation allows for the seamless adaptation of well-established 2D image/video techniques, enabling efficient and effective processing and analysis of 3D point cloud sequences. To achieve such re-organization, we design a self-supervised learning pipeline that is geometrically regularized and driven by self-reconstructive and deformation field learning objectives. Additionally, we construct SPCV-based frameworks for both low-level and high-level 3D point cloud sequence processing and analysis tasks, including action recognition, temporal interpolation, and compression. Extensive experiments demonstrate the versatility and superiority of the proposed SPCV, which has the potential to offer new possibilities for deep learning on unstructured 3D point cloud sequences. Code will be released at https://github.com/ZENGYIMING-EAMON/SPCV.

3D-CEUS/MRI-CEUS fusion imaging vs 2D-CEUS after locoregional therapies for hepatocellular carcinoma: a multicenter prospective study of therapeutic response evaluation.

OBJECTIVES: To compare the diagnostic accuracy of 3D contrast-enhanced ultrasound (CEUS)/MRI-CEUS fusion imaging with 2D-CEUS in assessing the response of hepatocellular carcinoma (HCC) to locoregional therapies in a multicenter prospective study. MATERIALS AND METHODS: A consecutive series of patients with HCC scheduled for locoregional treatment were enrolled between April 2021 and March 2023. Patients were randomly divided into 3D-CEUS/MRI-CEUS fusion imaging group (3D/fusion group) or 2D-CEUS group (2D group). CEUS was performed 1 week before and 4-6 weeks after locoregional treatment. Contrast-enhanced MRI (CE-MRI) 4-6 weeks after treatment was set as the reference standard. CEUS images were evaluated for the presence or absence of viable tumors. Diagnostic performance criteria, including sensitivity, specificity, accuracy, and area under the curve (AUC), were determined for each modality. RESULTS: A total of 140 patients were included, 70 patients in the 2D group (mean age, 60.2 ± 10.4 years) and 70 patients in the 3D/fusion group (mean age, 59.8 ± 10.6 years). The sensitivity of the 3D/fusion group was 100.0% (95% CI: 75.9, 100.0), higher than that of the 2D group (55.6%, 95% CI: 22.7, 84.7; p = 0.019). The specificity of the 3D/fusion group was 96.3% (95% CI: 86.2, 99.4), which was comparable to that of the 2D group (98.4%, 95% CI: 90.0, 99.9; p = 0.915). The AUC of the 3D/fusion group was 0.98 (95% CI: 0.95, 1.00), higher than that of the 2D group (0.77, 95% CI: 0.56, 0.98; p = 0.020). CONCLUSION: 3D-CEUS/MRI-CEUS fusion imaging exhibits superior diagnostic accuracy in evaluating the treatment response to locoregional therapies for HCC. CLINICAL RELEVANCE STATEMENT: 3D-CEUS/MRI-CEUS fusion imaging can be applied for post-treatment assessment of residual tumors in HCC undergoing locoregional treatment, offering potential benefits in terms of accurate diagnosis and clinical management. KEY POINTS: Evaluating for HCC recurrence following locoregional therapy is important. 3D-CEUS/MRI-CEUS fusion imaging achieved a higher sensitivity than 2D-CEUS in assessing residual tumors after locoregional therapies. 3D-CEUS/MRI-CEUS fusion imaging can help clinicians intervene early in residual HCC lesions after locoregional treatment.

Molecular understanding of the self-assembly of an N-isopropylacrylamide delivery system for the loading and temperature-dependent release of curcumin.

Global changes and drug abuse are forcing humanity to face various disease problems, and alternative therapies with safe natural substances have important research value. This paper combines various techniques in quantum chemical calculations and molecular simulations to provide molecular-level insight into the dynamics of the self-assembly of N-isopropylacrylamide (NIPAM) for loading curcumin (CUR). The results indicate that increasing the chain length of NIPAM molecules reduces their efficiency in encapsulating and locking CUR, and electrostatic interactions and van der Waals interactions are the main driving forces behind the evolution of system configurations in these processes. The isopropyl groups of NIPAM and the two phenolic ring planes of CUR are the main contact areas for the interaction between the two types of molecules. The thermosensitive effect of NIPAM can alter the distribution of isopropyl groups in NIPAM molecules around CUR. As a result, when the temperature rises from ambient temperature (300 K) to human characteristic temperature (310 K), the NIPAM-CUR interactions and radial distribution functions suggest that body temperature is more suitable for drug release. Our findings offer a vital theoretical foundation and practical guidance for researchers to develop temperature-sensitive drug delivery systems tailored for CUR, addressing its clinical application bottleneck.

Glucose-6-phosphate dehydrogenase maintains redox homeostasis and biosynthesis in LKB1-deficient KRAS-driven lung cancer.

Cancer cells depend on nicotinamide adenine dinucleotide phosphate (NADPH) to combat oxidative stress and support reductive biosynthesis. One major NADPH production route is the oxidative pentose phosphate pathway (committed step: glucose-6-phosphate dehydrogenase, G6PD). Alternatives exist and can compensate in some tumors. Here, using genetically-engineered lung cancer mouse models, we show that G6PD ablation significantly suppresses KrasG12D/+;Lkb1-/- (KL) but not KrasG12D/+;P53-/- (KP) lung tumorigenesis. In vivo isotope tracing and metabolomics reveal that G6PD ablation significantly impairs NADPH generation, redox balance, and de novo lipogenesis in KL but not KP lung tumors. Mechanistically, in KL tumors, G6PD ablation activates p53, suppressing tumor growth. As tumors progress, G6PD-deficient KL tumors increase an alternative NADPH source from serine-driven one carbon metabolism, rendering associated tumor-derived cell lines sensitive to serine/glycine depletion. Thus, oncogenic driver mutations determine lung cancer dependence on G6PD, whose targeting is a potential therapeutic strategy for tumors harboring KRAS and LKB1 co-mutations.

A Diffusion Model Translator for Efficient Image-to-Image Translation.

Applying diffusion models to image-to-image translation (I2I) has recently received increasing attention due to its practical applications. Previous attempts inject information from the source image into each denoising step for an iterative refinement, thus resulting in a time-consuming implementation. We propose an efficient method that equips a diffusion model with a lightweight translator, dubbed a Diffusion Model Translator (DMT), to accomplish I2I. Specifically, we first offer theoretical justification that in employing the pioneering DDPM work for the I2I task, it is both feasible and sufficient to transfer the distribution from one domain to another only at some intermediate step. We further observe that the translation performance highly depends on the chosen timestep for domain transfer, and therefore propose a practical strategy to automatically select an appropriate timestep for a given task. We evaluate our approach on a range of I2I applications, including image stylization, image colorization, segmentation to image, and sketch to image, to validate its efficacy and general utility. The comparisons show that our DMT surpasses existing methods in both quality and efficiency. Code will be made publicly available.

Identification of chalcone analogues as anti-inflammatory agents through the regulation of NF-κB and JNK activation.

To develop new anti-inflammatory agents with improved pharmaceutical profiles, a series of chalcone analogues were designed and synthesized. In vitro anti-inflammatory activity of these compounds was evaluated by screening their inhibitory effects on NO production in RAW264.7 cell lines. The most promising compounds 3h and 3l were selected for further investigation by assessment of their dose-dependent inhibitory activity against cytokines such as TNF-α, IL-1ß, and IL-6 and PGE2 release. The further study also indicated that 3h and 3l could significantly suppress the expression of iNOS and COX-2 through the NF-κB/JNK signaling pathway. Furthermore, compounds 3h and 3l could also remarkably inhibit the mRNA expression of inflammation-related genes. Meanwhile, 3h could also down-regulate ROS production. Docking simulation was conducted to position compounds 3h and 3l into the iNOS binding site to predict the probable binding mode. In conclusion, this series of chalcone analogues with reasonable drug-likeness obtained via in silico rapid prediction can be used as promising lead candidates.

Computing Smooth and Integrable Cross Fields via Iterative Singularity Adjustment.

We propose a new method for computing smooth and integrable cross fields on 2D and 3D surfaces. We first compute smooth cross fields by minimizing the Dirichlet energy. Unlike the existing optimization based approaches, our method determines the singularity configuration, i.e., the number of singularities, their locations and indices, via iteratively adjusting singularities. The singularities can move, merge and split, as like charges repel and unlike charges attract. Once all singularities stop moving, we obtain a cross field with (locally) lowest Dirichlet energy. In simply connected domains, such a cross field is guaranteed to be integrable. However, this property does not hold in multiply connected domains. To make a smooth cross field integrable, we construct a vector field c, which characterizes how far the cross field is away from a curl-free field. Then we optimize the locations of singularities by moving them along the field lines of c. Our method is fundamentally different from the existing integer programming-based approaches, since it does not require any special numerical solver. It is fully automatic and also has a parameter to control the number of singularities. Our method is well suited for smooth models in which exact boundary alignment and sparse hard directional constraints are desired, and can guide seamless conformal parameterization and T-junction-free quadrangulation. We will make the source code publicly available.

Mapping of lymph node metastasis from esophageal squamous cell carcinoma after neoadjuvant treatment: a prospective analysis from a high-volume institution in China.

The study aimed to describe the prevalence of lymph node metastases per lymph node station for esophageal squamous cell carcinoma (ESCC) after neoadjuvant treatment. Clinicopathological variables of ESCC patients were retrieved from the prospective database of the Surgical Esophageal Cancer Patient Registry in West China Hospital, Sichuan University. A two-field lymphadenectomy was routinely performed, and an extensive three-field lymphadenectomy was performed if cervical lymph node metastasis was suspected. According to AJCC/UICC 8, lymph node stations were investigated separately. The number of patients with metastatic lymph nodes divided by those who underwent lymph node dissection at that station was used to define the percentage of patients with lymph node metastases. Data are also separately analyzed according to the pathological response of the primary tumor, neoadjuvant treatment regimens, pretreatment tumor length, and tumor location. Between January 2019 and March 2023, 623 patients who underwent neoadjuvant therapy followed by transthoracic esophagectomy were enrolled. Lymph node metastases were found in 212 patients (34.0%) and most frequently seen in lymph nodes along the right recurrent nerve (10.1%, 58/575), paracardial station (11.4%, 67/587), and lymph nodes along the left gastric artery (10.9%, 65/597). For patients with pretreatment tumor length of >4 cm and non-pathological complete response of the primary tumor, the metastatic rate of the right lower cervical paratracheal lymph nodes is 10.9% (10/92) and 10.6% (11/104), respectively. For patients with an upper thoracic tumor, metastatic lymph nodes were most frequently seen along the right recurrent nerve (14.2%, 8/56). For patients with a middle thoracic tumor, metastatic lymph nodes were most commonly seen in the right lower cervical paratracheal lymph nodes (10.3%, 8/78), paracardial lymph nodes (10.2%, 29/285), and lymph nodes along the left gastric artery (10.4%, 30/289). For patients with a lower thoracic tumor, metastatic lymph nodes were most frequently seen in the paracardial station (14.2%, 35/247) and lymph nodes along the left gastric artery (13.1%, 33/252). The study precisely determined the distribution of lymph node metastases in ESCC after neoadjuvant treatment, which may help to optimize the extent of lymphadenectomy in the surgical management of ESCC patients after neoadjuvant therapy.

Prognostic Value of the Gustave Roussy Immune Score in Lung Cancer: A Meta-Analysis.

PURPOSE: To clarify the prognostic role of the Gustave Roussy immune (GRIm) score in lung cancer. METHODS: The PubMed, Embase, Web of Science, and China National Knowledge Infrastructure databases were searched up to March 30, 2024. The primary outcomes included overall survival (OS) and progression-free survival (PFS). Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to evaluate the associations between the GRIm score and survival, and subgroup analyses were performed based on pathological type (non-small cell lung cancer vs. small cell lung cancer), tumor stage (advanced vs. limited stage) and treatment approach (immune checkpoint inhibitor vs. surgery vs. chemotherapy). RESULTS: Eight studies with 1,333 participants were included. The pooled results showed that a higher GRIm score predicted worse OS (HR = 1.96, 95% CI: 1.54-2.49, P < 0.001) and PFS (HR = 1.64, 95% CI: 1.22-2.21, P = 0.001). Subgroup analyses for OS and PFS showed similar results. However, subgroup analyses for PFS indicated that the association between the GRIm score and PFS was nonsignificant among patients with small cell lung cancer (P = 0.114) and among patients treated with chemotherapy (P = 0.276). CONCLUSION: The GRIm score might serve as a novel prognostic factor for lung cancer. Additional studies are still needed to verify these findings.

RESPIRATION DEFECTS LIMIT SERINE SYNTHESIS REQUIRED FOR LUNG CANCER GROWTH AND SURVIVAL.

Mitochondrial function is important for both energetic and anabolic metabolism. Pathogenic mitochondrial DNA (mtDNA) mutations directly impact these functions, resulting in the detrimental consequences seen in human mitochondrial diseases. The role of pathogenic mtDNA mutations in human cancers is less clear; while pathogenic mtDNA mutations are observed in some cancer types, they are almost absent in others. We report here that the proofreading mutant DNA polymerase gamma ( PolG D256A ) induced a high mtDNA mutation burden in non-small-cell lung cancer (NSCLC), and promoted the accumulation of defective mitochondria, which is responsible for decreased tumor cell proliferation and viability and increased cancer survival. In NSCLC cells, pathogenic mtDNA mutations increased glycolysis and caused dependence on glucose. The glucose dependency sustained mitochondrial energetics but at the cost of a decreased NAD+/NADH ratio that inhibited de novo serine synthesis. Insufficient serine synthesis, in turn, impaired the downstream synthesis of GSH and nucleotides, leading to impaired tumor growth that increased cancer survival. Unlike tumors with intact mitochondrial function, NSCLC with pathogenic mtDNA mutations were sensitive to dietary serine and glycine deprivation. Thus, mitochondrial function in NSCLC is required specifically to sustain sufficient serine synthesis for nucleotide production and redox homeostasis to support tumor growth, explaining why these cancers preserve functional mtDNA. In brief: High mtDNA mutation burden in non-small-cell lung cancer (NSCLC) leads to the accumulation of respiration-defective mitochondria and dependency on glucose and glycolytic metabolism. Defective respiratory metabolism causes a massive accumulation of cytosolic nicotinamide adenine dinucleotide + hydrogen (NADH), which impedes serine synthesis and, thereby, glutathione (GSH) and nucleotide synthesis, leading to impaired tumor growth and increased survival. Highlights: Proofreading mutations in Polymerase gamma led to a high burden of mitochondrial DNA mutations, promoting the accumulation of mitochondria with respiratory defects in NSCLC.Defective respiration led to reduced proliferation and viability of NSCLC cells increasing survival to cancer.Defective respiration caused glucose dependency to fuel elevated glycolysis.Altered glucose metabolism is associated with high NADH that limits serine synthesis, leading to impaired GSH and nucleotide production.Mitochondrial respiration defects sensitize NSCLC to dietary serine/glycine starvation, further increasing survival.

Cornuside ameliorates cognitive impairments via RAGE/TXNIP/NF-κB signaling in Aß1-42 induced Alzheimer's disease mice.

Cornuside has been discovered to improve learning and memory in AD mice, however, its underlying mechanism was not fully understood. In the present study, we established an AD mice model by intracerebroventricular injection of Aß1-42, which were treated with cornuside (3, 10, 30 mg/kg) for 2 weeks. Cornuside significantly ameliorated cognitive function of AD mice in series of behavioral tests, including Morris water maze test, nest building test, novel object recognition test and step-down test. Additionally, cornuside could attenuate neuronal injury, and promote cholinergic synaptic transmission by restoring the level of acetylcholine (ACh) via inhibiting acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE), as well as facilitating choline acetyltransferase (ChAT). Furthermore, cornuside inhibited oxidative stress levels amplified as decreased malondialdehyde (MDA), by inhibiting TXNIP expression, improving total anti-oxidative capacity (TAOC), raising activities of superoxide dismutase (SOD) and catalase (CAT). Cornuside also reduced the activation of microglia and astrocytes, decreased the level of proinflammatory factors TNF-α, IL-6, IL-1ß, iNOS and COX2 via interfering RAGE-mediated IKK-IκB-NF-κB phosphorylation. Similar anti-oxidative and anti-inflammatory effects were also found in LPS-stimulated BV2 cells via hampering RAGE-mediated TXNIP activation and NF-κB nuclear translocation. Virtual docking revealed that cornuside could interact with the active pocket of RAGE V domain directly. In conclusion, cornuside could bind to the RAGE directly impeding the interaction of Aß and RAGE, and cut down the expression of TXNIP inhibiting ROS production and oxidative stress, as well as hamper NF-κB p65 mediated the inflammation.

Supramolecular interaction between berberine hydrochloride and baicalin in aqueous solution: Reaction kinetics, spectral analysis and dynamic simulation.

The current study presents a comprehensive investigation on the precipitation reaction and supramolecular interactions between berberine hydrochloride (BBR) and baicalin (BA) in an aqueous system. Utilizing a combination of multi-spectral analytical techniques and molecular dynamic simulations, we elucidated the mechanism of the complexion process. The precipitate formation was observed within a drug concentration range of 0.1-1.0 mM, and a 1:1 stoichiometry ratio of BBR to BA was established by the Job's plot method. Morphological and structural characterizations of the precipitates were conducted using DSC, FTIR and PXRD. Additionally, UV-Vis absorption and 1H NMR spectroscopy were employed to compare the spectral characteristics of the precipitates with those of individual drug solution. Molecular dynamic simulations further dissected the intermolecular interactions and self-assembly mechanisms. The precipitates formed were amorphous microparticles with an average diameter of approximately 20 µm, primarily stabilized by hydrogen bonding and π-π stacking. This study contributes foundational insights into the supramolecular interactions between BBR and BA, therefore facilitated a better understanding of the precipitation process involving flavonoid-alkaloid pairs in mixed aqueous solutions.

PERF: Panoramic Neural Radiance Field from a Single Panorama.

Neural Radiance Field (NeRF) has achieved substantial progress in novel view synthesis given multi-view images. Recently, some works have attempted to train a NeRF from a single image with 3D priors. They mainly focus on a limited field of view with a few occlusions, which greatly limits their scalability to real-world 360-degree panoramic scenarios with large-size occlusions. In this paper, we present PERF, a 360-degree novel view synthesis framework that trains a panoramic neural radiance field from a single panorama. Notably, PERF allows 3D roaming in a complex scene without expensive and tedious image collection. To achieve this goal, we propose a novel collaborative RGBD inpainting method and a progressive inpainting-and-erasing method to lift up a 360-degree 2D scene to a 3D scene. Specifically, we first predict a panoramic depth map as initialization given a single panorama and reconstruct visible 3D regions with volume rendering. Then we introduce a collaborative RGBD inpainting approach into a NeRF for completing RGB images and depth maps from random views, which is derived from an RGB Stable Diffusion model and a monocular depth estimator. Finally, we introduce an inpainting-and-erasing strategy to avoid inconsistent geometry between a newly-sampled view and reference views. The two components are integrated into the learning of NeRFs in a unified optimization framework and achieve promising results. Extensive experiments on Replica and a new dataset PERF-in-the-wild demonstrate the superiority of our PERF over state-of-the-art methods. Our PERF can be widely used for real-world applications, such as panorama-to-3D, text-to-3D, and 3D scene stylization applications. Project page and code are available at https://github.com/perf-project/PeRF.

NeRFBuff: Fast Neural Rendering via Inter-frame Feature Buffering.

Neural radiance fields (NeRF) have demonstrated impressive performance in novel view synthesis, but are still slow to render complex scenes at a high resolution. We introduce a novel method to boost the NeRF rendering speed by utilizing the temporal coherence between consecutive frames. Rather than computing features of each frame entirely from scratch, we reuse the coherent information (e.g., density and color) computed from the previous frames to help render the current frame, which significantly boosts rendering speed. To effectively manage the coherent information of previous frames, we introduce a history buffer with a multiple-plane structure, which is built online and updated from old frames to new frames. We name this buffer as multiple plane buffer (MPB). With this MPB, a new frame can be efficiently rendered using the warped features from previous frames. Extensive experiments on the NeRF-Synthetic, LLFF, and Mip-NeRF-360 datasets demonstrate that our method significantly boosts rendering efficiency and achieves 4× speedup on real-world scenes compared to the baseline methods while preserving competitive rendering quality.

The novel circ_0004674/miR-139-5p/ZBTB2 regulatory cascade inhibits the development of oral squamous cell carcinoma.

BACKGROUND: Circular RNAs (circRNAs) are an intriguing family of RNA molecules due to their crucial roles in the pathogenesis of oral squamous cell carcinoma (OSCC). Here, we sought to define the action of human circ_0004674 in OSCC progression. METHODS: The functional role of circ_0004674 was validated by determining its effect on cell growth, apoptosis, and tube formation ability of OSCC cells. For protein quantification, a western blot or immunohistochemistry method was applied. The interaction between miR-139-5p and circ_0004674 or zinc finger and BTB domain containing 2 (ZBTB2) was predicted by online algorithms, and their relationships were confirmed by dual-luciferase reporter and RIP assays. Xenograft models were established to uncover circ_0004674's role in tumor growth. RESULTS: Circ_0004674 expression was upregulated in OSCC. Functionally, knocking down circ_0004674 led to suppressed OSCC cell progression in vitro and delayed tumor growth in vivo. Mechanistically, circ_0004674 post-transcriptionally controlled ZBTB2 expression by competitively pairing to miR-139-5p. Furthermore, the deficiency of miR-139-5p abated circ_0004674 silencing-mediated OSCC cell progression repression, and augmentation of ZBTB2 reversed the anticancer effect of miR-139-5p on OSCC. CONCLUSION: Our findings uncover a novel regulatory cascade, the circ_0004674/miR-139-5p/ZBTB2 axis, with the ability to affect OSCC development in vitro and in vivo, providing a potential opportunity for development of OSCC therapy.

Insulin resistance in NSCLC: unraveling the link between development, diagnosis, and treatment.

Lung cancer is responsible for the highest number of cancer-related deaths, with non-small cell lung cancer (NSCLC) being the most prevalent subtype. A critical aspect of managing lung cancer is reducing morbidity and mortality rates among NSCLC patients. Identifying high-risk factors for lung cancer and facilitating early diagnosis are invaluable in achieving this objective. Recent research has highlighted the association between insulin resistance and the development of NSCLC, further emphasizing its significance in the context of lung cancer. It has been discovered that improving insulin resistance can potentially inhibit the progression of lung cancer. Consequently, this paper aims to delve into the occurrence of insulin resistance, the mechanisms underlying its involvement in lung cancer development, as well as its potential value in predicting, assessing, and treating lung cancer.

Analysis of genes characterizing chronic thrombosis and associated pathways in chronic thromboembolic pulmonary hypertension.

PURPOSE: In chronic thromboembolic pulmonary hypertension (CTEPH), fibrosis of thrombi in the lumen of blood vessels and obstruction of blood vessels are important factors in the progression of the disease. Therefore, it is important to explore the key genes that lead to chronic thrombosis in order to understand the development of CTEPH, and at the same time, it is beneficial to provide new directions for early identification, disease prevention, clinical diagnosis and treatment, and development of novel therapeutic agents. METHODS: The GSE130391 dataset was downloaded from the Gene Expression Omnibus (GEO) public database, which includes the full gene expression profiles of patients with CTEPH and Idiopathic Pulmonary Arterial Hypertension (IPAH). Differentially Expressed Genes (DEGs) of CTEPH and IPAH were screened, and then Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) functional enrichment analyses were performed on the DEGs; Weighted Gene Co-Expression Network Analysis (WGCNA) to screen the key gene modules and take the intersection genes of DEGs and the key module genes in WGCNA; STRING database was used to construct the protein-protein interaction (PPI) network; and cytoHubba analysis was performed to identify the hub genes. RESULTS: A total of 924 DEGs were screened, and the MEturquoise module with the strongest correlation was selected to take the intersection with DEGs A total of 757 intersecting genes were screened. The top ten hub genes were analyzed by cytoHubba: IL-1B, CXCL8, CCL22, CCL5, CCL20, TNF, IL-12B, JUN, EP300, and CCL4. CONCLUSION: IL-1B, CXCL8, CCL22, CCL5, CCL20, TNF, IL-12B, JUN, EP300, and CCL4 have diagnostic and therapeutic value in CTEPH disease, especially playing a role in chronic thrombosis. The discovery of NF-κB, AP-1 transcription factors, and TNF signaling pathway through pivotal genes may be involved in the disease progression process.

Multiparametric US for Identifying Metabolic Dysfunction-associated Steatohepatitis: A Prospective Multicenter Study.

Background Noninvasive evaluation of metabolic dysfunction-associated fatty liver disease (MAFLD) with multiparametric US is essential, but multicenter studies are lacking. Purpose To evaluate the ability of multiparametric US with attenuation imaging (ATI) and two-dimensional (2D) shear-wave elastography (SWE) for predicting metabolic dysfunction-associated steatohepatitis (MASH) in participants with MAFLD, regardless of hepatitis B virus infection status. Materials and Methods This prospective cross-sectional multicenter study of consecutive adults with MAFLD who underwent multiparametric US with ATI and 2D SWE, as well as liver biopsy, from September 2020 to June 2022 was conducted in 12 tertiary hospitals in China. Multivariable logistic regression was performed to assess risk factors associated with MASH. Area under the receiver operating characteristic curve (AUC) analysis was used to evaluate diagnostic performance in predicting MASH in training and validation groups (6:4 ratio of participants), and for a post hoc subgroup analysis of hepatitis B virus infection and diabetes. Results A total of 424 participants (median age, 47 years; IQR, 34-59 years; 244 male) were evaluated, including 332 participants (78%) with MASH and 92 (22%) without. Attenuation coefficient (AC) (odds ratio [OR], 3.32 [95% CI: 1.94, 5.71]; P < .001), alanine aminotransferase (ALT) level (OR, 4.42 [95% CI: 1.78, 10.94]; P = .001), and international normalized ratio (INR) (OR, 0.59 [95% CI: 0.37, 0.95]; P = .03) were independently associated with MASH. A combined model (AC, ALT, and INR) had AUCs of 0.85 (95% CI: 0.79, 0.91) and 0.77 (95% CI: 0.69, 0.85) for predicting MASH in the training and validation groups, respectively. AUC values for the subgroups with and without diabetes were 0.83 (95% CI: 0.72, 0.94) and 0.81 (95% CI: 0.75, 0.87) and for the subgroups with and without hepatitis B were 0.82 (95% CI: 0.74, 0.90) and 0.79 (95% CI: 0.71, 0.87), respectively. Conclusion A model combining AC, ALT level, and INR showed good discrimination ability for predicting MASH in participants with MAFLD. Clinical trial registration no. NCT04551716 © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Reuter in this issue.