Melanin-Targeting Radiotracers and Their Preclinical, Translational, and Clinical Status: From Past to Future.

Melanin is one of the representative biomarkers of malignant melanoma and a potential target for diagnosis and therapy. With advancements in chemistry and radiolabeling technologies, promising strides have been made to synthesize radiolabeled melanin-binding molecules for various applications. We present an overview of melanin-targeted radiolabeled molecules and compare their features reported in preclinical studies. Clinical practice and trials are also discussed to elaborate on the safety and validity of the probes, and expanded applications beyond melanoma are reviewed. Melanin-targeted imaging holds potential value in the diagnosis, staging, and prognostic assessment of melanoma and other applications. Melanin-targeted radionuclide therapy possesses immense potential but requires more clinical validation. Furthermore, an intriguing avenue for future research involves expanding the application scope of melanin-targeted probes and exploring their value.

Ganoderic acid A ameliorates depressive-like behaviors in CSDS mice: Insights from proteomic profiling and molecular mechanisms.

OBJECTIVE: Ganoderic Acid A (GAA), a primary bioactive component in Ganoderma, has demonstrated ameliorative effects on depressive-like behaviors in a Chronic Social Defeat Stress (CSDS) mouse model. This study aims to elucidate the underlying molecular mechanisms through proteomic analysis. METHODS: C57BL/6 J mice were allocated into control (CON), chronic social defeat stress (CSDS), GAA, and imipramine (IMI) groups. Post-depression induction via CSDS, the GAA and IMI groups received respective treatments of GAA (2.5 mg/kg) and imipramine (10 mg/kg) for five days. Behavioral assessments utilized standardized tests. Proteins from the prefrontal cortex were analyzed using LC-MS, with further examination via bioinformatics and PRM for differential expression. Western blot analysis confirmed protein expression levels. RESULTS: Chronic social defeat stress (CSDS) induced depressive-like behaviors in mice, which were significantly alleviated by GAA treatment, comparably to imipramine (IMI). Proteomic analysis identified distinct proteins in control (305), GAA-treated (949), and IMI-treated (289) groups. Enrichment in mitochondrial and synaptic proteins was evident from GO and PPI analyses. PRM analysis revealed significant expression changes in proteins crucial for mitochondrial and synaptic functions (namely, Naa30, Bnip1, Tubgcp4, Atxn3, Carmil1, Nup37, Apoh, Mrpl42, Tprkb, Acbd5, Dcx, Erbb4, Ppp1r2, Fam3c, Rnf112, and Cep41). Western blot validation in the prefrontal cortex showed increased levels of Mrpl42, Dcx, Fam3c, Ppp1r2, Rnf112, and Naa30 following GAA treatment. CONCLUSION: GAA exhibits potential antidepressant properties, with its action potentially tied to the modulation of synaptic functions and mitochondrial activities.

Transcatheter tricuspid valve replacement with LuX-valve device: Overview of key echocardiographic considerations.

Tricuspid regurgitation is a common valve disease with high incidence and poor prognosis. For elderly patients and those with a history of open heart surgery, second thoracotomy and valve replacement carry a high risk. Transcatheter tricuspid valve replacement (TTVR) has become an alternative treatment for patients with high surgical risk. LuX-Valve is a novel self-expandable valve that does not rely on radial force to anchor the valve annulus. The preliminary results have been satisfactory, and this technology is gradually being adopted in China and around the world. Successful implementation of this technique depends on echocardiographic preoperative screening, intraoperative guidance, and postoperative follow-up. The purpose of this article is to provide a state-of-the-art review of the key points and technical considerations for preoperative screening, intraoperative guidance, and postoperative follow-up for TTVR.

Electrocardiogram-based prediction of conduction disturbances after transcatheter aortic valve replacement with convolutional neural network.

Aims: Permanent pacemaker implantation and left bundle branch block are common complications after transcatheter aortic valve replacement (TAVR) and are associated with impaired prognosis. This study aimed to develop an artificial intelligence (AI) model for predicting conduction disturbances after TAVR using pre-procedural 12-lead electrocardiogram (ECG) images. Methods and results: We collected pre-procedural 12-lead ECGs of patients who underwent TAVR at West China Hospital between March 2016 and March 2022. A hold-out testing set comprising 20% of the sample was randomly selected. We developed an AI model using a convolutional neural network, trained it using five-fold cross-validation and tested it on the hold-out testing cohort. We also developed and validated an enhanced model that included additional clinical features. After applying exclusion criteria, we included 1354 ECGs of 718 patients in the study. The AI model predicted conduction disturbances in the hold-out testing cohort with an area under the curve (AUC) of 0.764, accuracy of 0.743, F1 score of 0.752, sensitivity of 0.876, and specificity of 0.624, based solely on pre-procedural ECG images. The performance was better than the Emory score (AUC = 0.704), as well as the logistic (AUC = 0.574) and XGBoost (AUC = 0.520) models built with previously identified high-risk ECG patterns. After adding clinical features, there was an increase in the overall performance with an AUC of 0.779, accuracy of 0.774, F1 score of 0.776, sensitivity of 0.794, and specificity of 0.752. Conclusion: Artificial intelligence-enhanced ECGs may offer better predictive value than traditionally defined high-risk ECG patterns.

HIF2A mediates lineage transition to aggressive phenotype of cancer-associated fibroblasts in lung cancer brain metastasis.

Brain metastasis is the most devasting form of lung cancer. Recent studies highlight significant differences in the tumor microenvironment (TME) between lung cancer brain metastasis (LCBM) and primary lung cancer, which contribute significantly to tumor progression and drug resistance. Cancer-associated fibroblasts (CAFs) are the major component of pro-tumor TME with high plasticity. However, the lineage composition and function of CAFs in LCBM remain elusive. By reanalyzing single-cell RNA sequencing (scRNA-seq) data (GSE131907) from lung cancer patients with different stages of metastasis comprising primary lesions and brain metastasis, we found that CAFs undergo distinctive lineage transition during LCBM under a hypoxic situation, which is directly driven by hypoxia-induced HIF-2α activation. Transited CAFs enhance angiogenesis through VEGF pathways, trigger metabolic reprogramming, and promote the growth of tumor cells. Bulk RNA sequencing data was utilized as validation cohorts. Multiplex immunohistochemistry (mIHC) assay was performed on four paired samples of brain metastasis and their primary lung cancer counterparts to validate the findings. Our study revealed a novel mechanism of lung cancer brain metastasis featuring HIF-2α-induced lineage transition and functional alteration of CAFs, which offers potential therapeutic targets.

Sequential Scan-Based Single-Dimension Multi-Voxel System Matrix Calibration for Open-Sided Magnetic Particle Imaging.

Open-sided magnetic particle imaging (OS-MPI) has garnered significant interest due to its potential for interventional applications. However, the system matrix calibration in OS-MPI using sequential scans is a time-consuming task and susceptible to the low signal-to-noise ratio (SNR) resulting from the small calibration sample size. These challenges have hindered the practical implementation of system matrix-based reconstruction for sequentially scanned OS-MPI. To address these issues, we propose a novel calibration method, named sequential scan-based single-dimension multi-voxel calibration (SS-SDMVC), to efficiently obtain a high-SNR system matrix. This method was implemented in a cylindrical field of view (FOV), where a bar calibration sample parallel to the field-free line (FFL) was shifted along a fixed radial direction. A standard image reconstruction process was also introduced to verify the feasibility of SS-SDMVC. Through simulations, we analyzed the effects of noise levels and scanner imperfections on the SS-SDMVC-based reconstruction and demonstrated its robustness. In experiments, we compared the imaging performance of SS-SDMVC and the sequential scan-based traditional cubic-FOV SMC. The results showed that SS-SDMVC reduced the number of measurements by a factor of 210.94 and achieved higher reconstruction quality. Therefore, SS-SDMVC is expected to improve the reconstruction quality of human-scale or high-gradient FFL MPI scanners.

The efficacy of exercise training for improving body composition in patients with breast cancer: A systematic review and meta-analysis of randomized controlled trials.

OBJECTIVES: To evaluate the efficacy of exercise in improving body composition in patients with breast cancer; the effects of exercise on weight and BMI were evaluated as secondary outcomes. DATA SOURCES: Cochrane Library, EMBASE, PubMed and Web of Science were searched for randomized controlled trials published in English from database inception to 29 November 2023. METHODS: The effects of exercise on body composition in patients with breast cancer were explored. After separately extracting the data, two reviewers assessed the overall quality of the evidence as well as the methodological quality of the included studies. RESULTS: Fourteen studies with 1241 participants were included, of which 12 studies were eligible for meta-analysis. Exercise significantly reduced body fat (mean difference [MD], -0.33; 95% CI, -0.37 to -0.29; P < 0.00001) and increased lean mass (MD, 0.42; 95% CI, 0.34 to 0.49; P < 0.00001) in patients with breast cancer. Further, exercise intervention was associated with increased BMI of patients with breast cancer (MD, 0.03; 95% CI, 0.01 to 0.06; P = 0.01), while no significant difference in weight was detected between the exercise and the non-exercise groups. Subgroup analysis results showed that only resistance exercise reduced fat mass (MD, -0.22; 95% CI, -0.27 to -0.16; P < 0.00001). CONCLUSIONS: Exercise effectively improves body composition in patients with breast cancer. Clinicians should encourage patients to engage in exercise and develop optimized exercise prescriptions.

Automatic planning of maxillary anterior dental implant based on prosthetically guided and pose evaluation indicator.

PURPOSE: Preoperative planning of maxillary anterior dental implant is a prerequisite to ensuring that the implant achieves the proper three-dimensional (3D) pose, which is essential for its long-term stability. However, the current planning process is labor-intensive and subjective, relying heavily on the surgeon's experience. Consequently, this paper proposes an automatic method for computing the optimal pose of the dental implant. METHODS: The method adopts the principle of prosthetically guided dental implant placement. Initially, the prosthesis coordinate system is established to determine the implant candidate orientations. Subsequently, virtual slices of the maxilla in the buccal-palatal direction are generated according to the prosthesis position. By extracting feature points from the virtual slices, the implant candidate starting points are acquired. Then, a candidate pose set is obtained by combining these candidate starting points and orientations. Finally, a pose evaluation indicator is introduced to determine the optimal implant pose from this set. RESULTS: Twenty-two cases were utilized to validate the method. The results show that the method could determine an ideal pose for the dental implant, with the average minimum distance between the implant and the left tooth root, the right tooth root, the palatal side, and the buccal side being 2.57 ± 0.53 mm, 2.59 ± 0.65 mm, 0.74 ± 0.19 mm, 1.83 ± 0.16 mm, respectively. The planning time was less than 9 s. CONCLUSION: Unlike manual planning, the proposed method can efficiently and accurately complete maxillary anterior dental implant planning, providing a theoretical analysis of the success rate of the implant. Thus, it has great potential for future clinical application.

Prevalence and network structure of depression, insomnia and suicidality among mental health professionals who recovered from COVID-19: a national survey in China.

Psychiatric syndromes are common following recovery from Coronavirus Disease 2019 (COVID-19) infection. This study investigated the prevalence and the network structure of depression, insomnia, and suicidality among mental health professionals (MHPs) who recovered from COVID-19. Depression and insomnia were assessed with the Patient Health Questionnaire (PHQ-9) and Insomnia Severity Index questionnaire (ISI7) respectively. Suicidality items comprising suicidal ideation, suicidal plan and suicidal attempt were evaluated with binary response (no/yes) items. Network analyses with Ising model were conducted to identify the central symptoms of the network and their links to suicidality. A total of 9858 COVID-19 survivors were enrolled in a survey of MHPs. The prevalence of depression and insomnia were 47.10% (95% confidence interval (CI) = 46.09-48.06%) and 36.2% (95%CI = 35.35-37.21%), respectively, while the overall prevalence of suicidality was 7.8% (95%CI = 7.31-8.37%). The key central nodes included "Distress caused by the sleep difficulties" (ISI7) (EI = 1.34), "Interference with daytime functioning" (ISI5) (EI = 1.08), and "Sleep dissatisfaction" (ISI4) (EI = 0.74). "Fatigue" (PHQ4) (Bridge EI = 1.98), "Distress caused by sleep difficulties" (ISI7) (Bridge EI = 1.71), and "Motor Disturbances" (PHQ8) (Bridge EI = 1.67) were important bridge symptoms. The flow network indicated that the edge between the nodes of "Suicidality" (SU) and "Guilt" (PHQ6) showed the strongest connection (Edge Weight= 1.17, followed by "Suicidality" (SU) - "Sad mood" (PHQ2) (Edge Weight = 0.68)). The network analysis results suggest that insomnia symptoms play a critical role in the activation of the insomnia-depression-suicidality network model of COVID-19 survivors, while suicidality is more susceptible to the influence of depressive symptoms. These findings may have implications for developing prevention and intervention strategies for mental health conditions following recovery from COVID-19.

Reoxygenation Mitigates Intermittent Hypoxia-Induced Systemic Inflammation and Gut Microbiota Dysbiosis in High-Fat Diet-Induced Obese Rats.

Background: Obstructive sleep apnea (OSA) is a prevalent sleep breathing disorder characterized by intermittent hypoxia (IH), with continuous positive airway pressure (CPAP) as its standard treatment. However, the effects of intermittent hypoxia/reoxygenation (IH/R) on weight regulation in obesity and its underlying mechanism remain unclear. Gut microbiota has gained attention for its strong association with various diseases. This study aims to explore the combined influence of IH and obesity on gut microbiota and to investigate the impact of reoxygenation on IH-induced alterations. Methods: Diet-induced obese (DIO) rats were created by 8-week high-fat diet (HFD) feeding and randomly assigned into three groups (n=15 per group): normoxia (NM), IH (6% O2, 30 cycles/h, 8 h/day, 4 weeks), or hypoxia/reoxygenation (HR, 2-week IH followed by 2-week reoxygenation) management. After modeling and exposure, body weight and biochemical indicators were measured, and fecal samples were collected for 16S rRNA sequencing. Results: DIO rats in the IH group showed increased weight gain (p=0.0016) and elevated systemic inflammation, including IL-6 (p=0.0070) and leptin (p=0.0004). Moreover, IH rats exhibited greater microbial diversity (p<0.0167), and significant alterations in the microbial structure (p=0.014), notably the order Clostridiales, accompanied by an upregulation of bile acid metabolism predicted pathway (p=0.0043). Reoxygenation not only improved IH-exacerbated obesity, systemic inflammation, leptin resistance, and sympathetic activation, but also showed the potential to restore IH-induced microbial alterations. Elevated leptin levels were associated with Ruminococcaceae (p=0.0008) and Clostridiales (p=0.0019), while body weight was linked to Blautia producta (p=0.0377). Additionally, the abundance of Lactobacillus was negatively correlated with leptin levels (p=0.0006) and weight (p=0.0339). Conclusion: IH leads to gut dysbiosis and metabolic disorders, while reoxygenation therapy demonstrates a potentially protective effect by restoring gut homeostasis and mitigating inflammation. It highlights the potential benefits of CPAP in reducing metabolic risk among obese patients with OSA.

Amorphous Iridium Oxide-Integrated Anode Electrodes with Ultrahigh Material Utilization for Hydrogen Production at Industrial Current Densities.

Herein, ionomer-free amorphous iridium oxide (IrOx) thin electrodes are first developed as highly active anodes for proton exchange membrane electrolyzer cells (PEMECs) via low-cost, environmentally friendly, and easily scalable electrodeposition at room temperature. Combined with a Nafion 117 membrane, the IrOx-integrated electrode with an ultralow loading of 0.075 mg cm-2 delivers a high cell efficiency of about 90%, achieving more than 96% catalyst savings and 42-fold higher catalyst utilization compared to commercial catalyst-coated membrane (2 mg cm-2). Additionally, the IrOx electrode demonstrates superior performance, higher catalyst utilization and significantly simplified fabrication with easy scalability compared with the most previously reported anodes. Notably, the remarkable performance could be mainly due to the amorphous phase property, sufficient Ir3+ content, and rich surface hydroxide groups in catalysts. Overall, due to the high activity, high cell efficiency, an economical, greatly simplified and easily scalable fabrication process, and ultrahigh material utilization, the IrOx electrode shows great potential to be applied in industry and accelerates the commercialization of PEMECs and renewable energy evolution.

PKM2 promotes glioma progression by mediating CTNNB1 expression.

BACKGROUND: Glioma is a common intracranial tumor, exhibiting a high degree of aggressiveness and invasiveness. Pyruvate kinase M2 (PKM2) is overexpressed in glioma tissues. However, the biological role of PKM2 in glioma is unclear. METHODS: The qRT-PCR, CCK-8, Transwell, flow cytometry detection, western blot assays, ELISA assay, and pyruvate kinase activity assays were performed in glioma cells transfected with PKM2 shRNA to explore the function of PKM2 in glioma progression. Then, STRING website was used to predict the proteins that interacted with PKM2, and Co-IP assay was conducted to further validate their interaction. Subsequently, the above experiments were performed again to find the effect of catenin beta 1 (CTNNB1) overexpression on PKM2-deficient glioma cells. The transplanted tumor models were also established to further validate our findings. RESULTS: PKM2 was up-regulated in glioma cells and tissues. After inhibiting PKM2, the proliferation, migration, glycolysis, and EMT of glioma cells were significantly decreased, and the proportion of apoptosis was increased. The prediction results of STRING website showed that CTNNB1 and PKM2 had the highest interaction score. The correlation between CTNNB1 and PKM2 was further confirmed by Co-IP test. PKM2 knockdown suppressed glioma cell proliferation, migration, glycolysis, and EMT, while CTNNB1 overexpression rescued these inhibitory effects. Correspondingly, PKM2 knockdown inhibited glioma growth in vivo. CONCLUSION: In summary, these findings indicated that PKM2 promotes glioma progression by mediating CTNNB1 expression, providing a possible molecular marker for the clinical management of gliomas.

Non-centrosymmetric topological phase probed by non-linear Hall effect.

Non-centrosymmetric topological material has attracted intense attention due to its superior characteristics as compared with the centrosymmetric one, although probing the local quantum geometry in non-centrosymmetric topological material remains challenging. The non-linear Hall (NLH) effect provides an ideal tool to investigate the local quantum geometry. Here, we report a non-centrosymmetric topological phase in ZrTe5, probed by using the NLH effect. The angle-resolved and temperature-dependent NLH measurement reveals the inversion and ab-plane mirror symmetries breaking at <30 K, consistently with our theoretical calculation. Our findings identify a new non-centrosymmetric phase of ZrTe5 and provide a platform to probe and control local quantum geometry via crystal symmetries.

Highly controlled synthesis of symmetrically branched tripod and pentapod nanocrystals with enhanced photocatalytic performance.

Anisotropic nanostructures with tunable optical properties induced by controllable size and symmetry have attracted much attention in many applications. Herein, we report a controlled synthesis of symmetrically branched AuCu alloyed nanocrystals. By varying Au:Cu atom ratio in precursor, Y-shaped tripods with three-fold symmetry and star-shaped pentapods with five-fold symmetry are synthesized, respectively. The growth mechanism of AuCu tripods from icosahedral seeds and AuCu pentapods from decahedral seeds is revealed. Aiming to excellent photocatalytic performance, CdS nanocrystals are controlled grown onto the sharp tips of AuCu tripods and pentapods. In addition, a carrier-selective blocking layer of Ag2S is introduced between AuCu and CdS, for achieving effective charge separation in AuCu-Ag2S-CdS nanohybrids. Through evaluating the photocatalytic performance by hydrogen generation experiments, the AuCu-Ag2S-CdS tripod nanocrystals exhibit an optimized hydrogen evolution rate of 2182 µmol·g-1·h-1. These findings will contribute greatly to the understanding of complex nanoparticle growth mechanism and provide a strategy for the design of anisotropic nanoalloys for widely photocatalytic applications.

Integrative analyses on the ciliates Colpoda illuminate the life history evolution of soil microorganisms.

Microorganisms play a central role in sustaining soil ecosystems and agriculture, and these functions are usually associated with their complex life history. Yet, the regulation and evolution of life history have remained enigmatic and poorly understood, especially in protozoa, the third most abundant group of organisms in the soil. Here, we explore the life history of a cosmopolitan species-Colpoda steinii. Our analysis has yielded a high-quality macronuclear genome for C. steinii, with size of 155 Mbp and 37,123 protein-coding genes, as well as mean intron length of ~93 bp, longer than most other studied ciliates. Notably, we identify two possible whole-genome duplication events in C. steinii, which may account for its genome being about twice the size of C. inflata's, another co-existing species. We further resolve the gene expression profiles in diverse life stages of C. steinii, which are also corroborated in C. inflata. During the resting cyst stage, genes associated with cell death and vacuole formation are upregulated, and translation-related genes are downregulated. While the translation-related genes are upregulated during the excystment of resting cysts. Reproductive cysts exhibit a significant reduction in cell adhesion. We also demonstrate that most genes expressed in specific life stages are under strong purifying selection. This study offers a deeper understanding of the life history evolution that underpins the extraordinary success and ecological functions of microorganisms in soil ecosystems.IMPORTANCEColpoda species, as a prominent group among the most widely distributed and abundant soil microorganisms, play a crucial role in sustaining soil ecosystems and promoting plant growth. This investigation reveals their exceptional macronuclear genomic features, including significantly large genome size, long introns, and numerous gene duplications. The gene expression profiles and the specific biological functions associated with the transitions between various life stages are also elucidated. The vast majority of genes linked to life stage transitions are subject to strong purifying selection, as inferred from multiple natural strains newly isolated and deeply sequenced. This substantiates the enduring and conservative nature of Colpoda's life history, which has persisted throughout the extensive evolutionary history of these highly successful protozoa in soil. These findings shed light on the evolutionary dynamics of microbial eukaryotes in the ever-fluctuating soil environments. This integrative research represents a significant advancement in understanding the life histories of these understudied single-celled eukaryotes.

Applicability of the generalized wind profile model over mountainous forests.

The analytical equation based on Monin-Obukhov (M-O) similarity theory (i.e., wind profile equation) has been adopted since 1970s for using in the prediction of wind vertical profile over flat terrains, which is mature and accurate. However, its applicability over complex terrains remains unknown. This applicability signifies the accuracy of the estimations of aerodynamic parameters for the boundary layer of non-flat terrain, such as zero-displacement height (d) and aerodynamic roughness length (z0), which will determine the accuracy of frequency correction and source area analysis in calculating carbon, water, and trace gas fluxes based on vorticity covariance method. Therefore, the validation of wind profile model in non-flat terrain is the first step to test whether the flux model needs improvement. We measured three-dimensional wind speed data by using the Ker Towers (three towers in a watershed) at Qingyuan Forest CERN in the Mountainous Region of east Liaoning Province, and compared them with data from Panjin Agricultural Station in the Liaohe Plain, to evaluate the applicability of a generalized wind profile model based on the Monin-Obukhov similarity theory on non-flat terrain. The results showed that the generalized wind profile model could not predict wind speeds accurately of three flux towers separately located in different sites, indicating that wind profile model was not suitable for predicting wind speeds in complex terrains. In the leaf-off and leaf-on periods, the coefficient of determination (R2) between observed and predicted wind speeds ranged from 0.12 to 0.30. Compared to measured values, the standard error of the predicted wind speeds was high up to 2 m·s-1. The predicted wind speeds were high as twice as field-measured wind speed, indicating substantial overestimation. Nevertheless, this model correctly predicted wind speeds in flat agricultural landscape in Panjin Agricultural Station. The R2 between observed wind speeds and predicted wind speed ranged from 0.90 to 0.93. The standard error between observed and predicted values was only 0.5 m·s-1. Results of the F-test showed that the root-mean-square error of the observed and predicted wind speeds in each secondary forest complex terrain was much greater than that in flat agricultural landscape. Terrain was the primary factor affecting the applicability of wind profile model, followed by seasonality (leaf or leafless canopy). The wind profile model was not applicable to the boundary-layer flows over forest canopies in complex terrains, because the d was underestimated or both the d and z0 were underestimated, resulting in inaccurate estimation of aerodynamic height.

LncRNA XIST modulates miR-328-3p ectopic expression in lung injury induced by tobacco-specific lung carcinogen NNK both in vitro and in vivo.

BACKGROUND AND PURPOSE: It is well acknowledged that tobacco-derived lung carcinogens can induce lung injury and even lung cancer through a complex mechanism. MicroRNAs (MiRNAs) are differentially expressed in tobacco-derived carcinogen nicotine-derived nitrosamine ketone (NNK)-treated A/J mice. EXPERIMENTAL APPROACH: RNA sequencing was used to detect the level of long non-coding RNAs (lncRNAs). Murine and human lung normal and cancer cells were used to evaluate the function of lncRNA XIST and miR-328-3p in vitro, and NNK-treated A/J mice were used to test their function in vivo. In vivo levels of miR-328-3p and lncRNA XIST were analysed, using in situ hybridization. miR-328-3p agomir and lncRNA XIST-specific siRNA were used to manipulate in vivo levels of miR-328-3p and lncRNA XIST in A/J mice. KEY RESULTS: LncRNA XIST was up-regulated in NNK-induced lung injury and dominated the NNK-induced ectopic miRNA expression in NNK-induced lung injury both in vitro and in vivo. Either lncRNA XIST silencing or miR-328-3p overexpression exerted opposing effects in lung normal and cancer cells regarding cell migration. LncRNA XIST down-regulated miR-328-3p levels as a miRNA sponge, and miR-328-3p targeted the 3'-UTR of FZD7 mRNA, which is ectopically overexpressed in lung cancer patients. Both in vivo lncRNA XIST silencing and miR-328 overexpression could rescue NNK-induced lung injury and aberrant overexpression of the lung cancer biomarker CK19 in NNK-treated A/J mice. CONCLUSIONS AND IMPLICATIONS: Our results highlight the promotive effect of lncRNA XIST in NNK-induced lung injury and elucidate its post-transcriptional mechanisms, indicating that targeting lncRNA XIST/miR-328-3p could be a potential therapeutic strategy to prevent tobacco carcinogen-induced lung injury in vivo.

Aspirin treatment for unruptured intracranial aneurysms: Focusing on its anti-inflammatory role.

Intracranial aneurysms (IAs), as a common cerebrovascular disease, claims a worldwide morbidity rate of 3.2%. Inflammation, pivotal in the pathogenesis of IAs, influences their formation, growth, and rupture. This review investigates aspirin's modulation of inflammatory pathways within this context. With IAs carrying significant morbidity and mortality upon IAs rupture and current interventions limited to surgical clipping and endovascular coiling, the quest for pharmacological options is imperative. Aspirin's role in cardiovascular prevention, due to its anti-inflammatory effects, presents a potential therapeutic avenue for IAs. In this review, we examine aspirin's efficacy in experimental models and clinical settings, highlighting its impact on the progression and rupture risks of unruptured IAs. The underlying mechanisms of aspirin's impact on IAs are explored, with its ability examined to attenuate endothelial dysfunction and vascular injury. This review may provide a theoretical basis for the use of aspirin, suggesting a promising strategy for IAs management. However, the optimal dosing, safety, and long-term efficacy remain to be established. The implications of aspirin therapy are significant in light of current surgical and endovascular treatments. Further research is encouraged to refine aspirin's clinical application in the management of unruptured IAs, with the ultimate aim of reducing the incidence of aneurysms rupture.

Learning to Sketch: A Neural Approach to Item Frequency Estimation in Streaming Data.

Recently, there has been a trend of designing neural data structures to go beyond handcrafted data structures by leveraging patterns of data distributions for better accuracy and adaptivity. Sketches are widely used data structures in real-time web analysis, network monitoring, and self-driving to estimate item frequencies of data streams within limited space. However, existing sketches have not fully exploited the patterns of the data stream distributions, making it challenging to tightly couple them with neural networks that excel at memorizing pattern information. Starting from the premise, we envision a pure neural data structure as a base sketch, which we term the meta-sketch, to reinvent the base structure of conventional sketches. The meta-sketch learns basic sketching abilities from meta-tasks constituted with synthetic datasets following Zipf distributions in the pre-training phase and can be quickly adapted to real (skewed) distributions in the adaption phase. The meta-sketch not only surpasses its competitors in sketching conventional data streams but also holds good potential in supporting more complex streaming data, such as multimedia and graph stream scenarios. Extensive experiments demonstrate the superiority of the meta-sketch and offer insights into its working mechanism.