Tailoring Mechanical Properties of a Ceramic Nanowire Aerogel with Pyrolytic Carbon for In Situ Resilience at 1400 °C.

Resilient ceramic aerogels with a unique combination of lightweight, good high-temperature stability, high specific area, and thermal insulation properties are known for their promising applications in various fields. However, the mechanical properties of traditional ceramic aerogels are often constrained by insufficient interlocking of the building blocks. Here, we report a strategy to largely increase the interlocking degree of the building blocks by depositing a pyrolytic carbon (PyC) coating onto Si3N4 nanowires. The results show that the mechanical performances of the Si3N4 nanowire aerogels are intricately linked to the microstructure of the PyC nodes. The compression resilience of the Si3N4@PyC nanowire aerogels increases with an increase of the interlayer cross-linking in PyC. Additionally, benefiting from the excellent high-temperature stability of PyC, the Si3N4@PyC nanowire aerogels demonstrate significantly superior in situ resilience up to 1400 °C. The integrated mechanical and high-temperature properties of the Si3N4@PyC nanowire aerogels make them highly appealing for applications in harsh conditions. The facile method of manipulating the microstructure of the nodes may offer a perspective for tailoring the mechanical properties of ceramic aerogels.

Rapid Mass Conversion for Environmental Microplastics of Diverse Shapes.

Rivers have been recognized as the primary conveyors of microplastics to the oceans, and seaward transport flux of riverine microplastics is an issue of global attention. However, there is a significant discrepancy in how microplastic concentration is expressed in field occurrence investigations (number concentration) and in mass flux (mass concentration). Of urgent need is to establish efficient conversion models to correlate these two important paradigms. Here, we first established an abundant environmental microplastic dataset and then employed a deep neural residual network (ResNet50) to successfully separate microplastics into fiber, fragment, and pellet shapes with 92.67% accuracy. We also used the circularity (C) parameter to represent the surface shape alteration of pellet-shaped microplastics, which always have a more uneven surface than other shapes. Furthermore, we added thickness information to two-dimensional images, which has been ignored by most prior research because labor-intensive processes were required. Eventually, a set of accurate models for microplastic mass conversion was developed, with absolute estimation errors of 7.1, 3.1, 0.2, and 0.9% for pellet (0.50 ≤ C < 0.75), pellet (0.75 ≤ C ≤ 1.00), fiber, and fragment microplastics, respectively; environmental samples have validated that this set is significantly faster (saves ∼2 h/100 MPs) and less biased (7-fold lower estimation errors) compared to previous empirical models.

Placebo effects of repetitive transcranial magnetic stimulation on negative symptoms and cognition in patients with schizophrenia spectrum disorders: a systematic review and meta-analysis.

Background: Negative symptoms and cognitive impairments are highly frequent in schizophrenia spectrum disorders (SSD), associated with adverse functional outcomes and quality of life. Repetitive transcranial magnetic stimulation (rTMS) has been considered a promising therapeutic option in SSD. However, placebo effects of rTMS on these symptoms remained unclear. Objective: To investigate placebo effects of rTMS on alleviating negative symptoms and cognitive impairment in patients with SSD and to explore potential moderators. Methods: We systematically searched five electronic databases up to 15 July 2023. Randomized, double-blind, sham-controlled trials investigating effects of rTMS on negative symptoms or cognition in patients with SSD were included. The pooled placebo effect sizes, represented by Hedges' g, were estimated using the random-effects model. Potential moderators were explored through subgroup analysis and meta-regression. Results: Forty-four randomized controlled trials with 961 patients (mean age 37.53 years; 28.1% female) in the sham group were included. Significant low-to-moderate pooled placebo effect sizes were observed for negative symptoms (g=0.44, p<0.001), memory (g=0.31, p=0.010), executive function (g=0.35, p<0.001), working memory (g=0.26, p=0.004), and processing speed (g=0.36, p=0.004). Subgroup analysis indicated that placebo effects were affected by sham stimulation methods, rTMS targeting approaches, and stimulation frequency. Conclusions: Placebo effects of rTMS on negative symptoms and cognition in patients with SSD are significant in a small-to-moderate magnitude, which might be mediated by rTMS parameters. Our findings will provide new insights for practitioners to further optimize and establish standardized rTMS protocols for future RCTs tackling cardinal symptoms in SSD. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/, identifier CRD42023390138.

Microplastics in different tissues of historical and live samples of endangered mega-fish (Acipenser sinensis) and their potential relevance to exposure pathways.

The Chinese sturgeon (Acipenser sinensis) is an endangered freshwater mega-fish (IUCN-red listed) that survives in the Yangtze River Basin, but the population of which has declined significantly in response to environmental pressures generated by human activities. In order to evaluate the interaction between Chinese sturgeon and microplastics (MPs) for the first time, we examined the gut and gills of historical samples (n = 27), in conjunction with the blood and mucus of live samples (n = 10), to explore the potential pathways involved in MP uptake. We detected MPs in 62.9 % of the field fish, with no significant difference between guts (mean=0.9 items/individual) and gills (mean=0.8 items/individual). The abundance of MPs in fish from 2017 was significantly higher than that from 2015 to 2016 with regards to both gills and gut samples. The size of MPs in gills was significantly smaller than those in guts, yet both contained mostly fibers (90.2 %). No MPs were confirmed in blood, however 62.5 % of mucus samples contained MPs. The MPs in mucus indicated the possibility of MPs entering Chinese sturgeons if their skins were damaged. The body size of Chinese sturgeons affected their MPs uptake by ingestion and inhalation, as less MPs were detected in the gut and gills of smaller individuals. Combining the evidence from historical and live samples, we revealed the presence of MPs in different tissues of Chinese sturgeon and their potential relevance to exposure pathways. Our work expands the understanding of multiple exposure pathways between MPs and long-lived mega-fish, while emphasizing the potential risks of long-term exposure in the field.

Improved brain metastases segmentation using generative adversarial network and conditional random field optimization mask R-CNN.

BACKGROUND: In radiotherapy, the delineation of the gross tumor volume (GTV) in brain metastases using computed tomography (CT) simulation localization is very important. However, despite the criticality of this process, a pronounced gap exists in the availability of tools tailored for the automatic segmentation of the GTV based on CT simulation localization images. PURPOSE: This study aims to fill this gap by devising an effective tool specifically for the automatic segmentation of the GTV using CT simulation localization images. METHODS: A dual-network generative adversarial network (GAN) architecture was developed, wherein the generator focused on refining CT images for more precise delineation, and the discriminator differentiated between real and augmented images. This architecture was coupled with the Mask R-CNN model to achieve meticulous GTV segmentation. An end-to-end training process facilitated the integration between the GAN and Mask R-CNN functionalities. Furthermore, a conditional random field (CRF) was incorporated to refine the initial masks generated by the Mask R-CNN model to ensure optimal segmentation accuracy. The performance was assessed using key metrics, namely, the Dice coefficient (DSC), intersection over union (IoU), accuracy, specificity, and sensitivity. RESULTS: The GAN+Mask R-CNN+CRF integration method in this study performs well in GTV segmentation. In particular, the model has an overall average DSC of 0.819 ± 0.102 and an IoU of 0.712 ± 0.111 in the internal validation. The overall average DSC in the external validation data is 0.726 ± 0.128 and the IoU is 0.640 ± 0.136. It demonstrates favorable generalization ability. CONCLUSION: The integration of the GAN, Mask R-CNN, and CRF optimization provides a pioneering tool for the sophisticated segmentation of the GTV in brain metastases using CT simulation localization images. The method proposed in this study can provide a robust automatic segmentation approach for brain metastases in the absence of MRI.

From metabolism to malignancy: the multifaceted role of PGC1α in cancer.

PGC1α, a central player in mitochondrial biology, holds a complex role in the metabolic shifts seen in cancer cells. While its dysregulation is common across major cancers, its impact varies. In some cases, downregulation promotes aerobic glycolysis and progression, whereas in others, overexpression escalates respiration and aggression. PGC1α's interactions with distinct signaling pathways and transcription factors further diversify its roles, often in a tissue-specific manner. Understanding these multifaceted functions could unlock innovative therapeutic strategies. However, challenges exist in managing the metabolic adaptability of cancer cells and refining PGC1α-targeted approaches. This review aims to collate and present the current knowledge on the expression patterns, regulators, binding partners, and roles of PGC1α in diverse cancers. We examined PGC1α's tissue-specific functions and elucidated its dual nature as both a potential tumor suppressor and an oncogenic collaborator. In cancers where PGC1α is tumor-suppressive, reinstating its levels could halt cell proliferation and invasion, and make the cells more receptive to chemotherapy. In cancers where the opposite is true, halting PGC1α's upregulation can be beneficial as it promotes oxidative phosphorylation, allows cancer cells to adapt to stress, and promotes a more aggressive cancer phenotype. Thus, to target PGC1α effectively, understanding its nuanced role in each cancer subtype is indispensable. This can pave the way for significant strides in the field of oncology.

Cortical Microhemorrhage Presentation of Small Vessel Primary Angiitis of the Central Nervous System.

OBJECTIVE: Primary angiitis of the central nervous system (PACNS) is a rare vasculitis restricted to the brain, spinal cord, and leptomeninges. This study aimed to describe the imaging characteristics of patients with small vessel PACNS (SV-PACNS) using 7 T magnetic resonance imaging (MRI). METHODS: This ongoing prospective observational cohort study included patients who met the Calabrese and Mallek criteria and underwent 7 T MRI scan. The MRI protocol includes T1-weighted magnetization-prepared rapid gradient echo imaging, T2 star weighted imaging, and susceptibility-weighted imaging. Two experienced readers independently reviewed the neuroimages. Clinical data were extracted from the electronic patient records. The findings were then applied to a cohort of patients with large vessel central nervous system (CNS) vasculitis. RESULTS: We included 21 patients with SV-PACNS from December 2021 to November 2023. Of these, 12 (57.14%) had cerebral cortical microhemorrhages with atrophy. The pattern with microhemorrhages was described in detail based on the gradient echo sequence, leading to the identification of what we have termed the "coral-like sign." The onset age of patients with coral-like sign (33.83 ± 9.93 years) appeared younger than that of patients without coral-like sign (42.11 ± 14.18 years) (P = 0.131). Furthermore, the cerebral lesions in patients with cortical microhemorrhagic SV-PACNS showed greater propensity toward bilateral lesions (P = 0.03). The coral-like sign was not observed in patients with large vessel CNS vasculitis. INTERPRETATION: The key characteristics of the coral-like sign represent cerebral cortical diffuse microhemorrhages with atrophy, which may be an important MRI pattern of SV-PACNS. ANN NEUROL 2024.

Phosphorus-rich CoP4@N-C nanoarrays for efficient nitrate-to-ammonia electroreduction.

The electrochemical nitrate reduction reaction (NO3-RR) is a novel green method for ammonia synthesis. However, the lack of sufficient catalysts has hindered the development of the NO3-RR. This research develops a transformation of porous CoP@N-C/CC into porous phosphorus-rich CoP4@N-C/CC through high-temperature calcination. Due to its unique phosphating-rich structure, CoP4@N-C/CC exhibits an excellent Faraday efficiency (FE: 92.3%) and NH3 yield (610.2 µmol h-1 cm-2). Such a catalyst with more P-P bonds can provide more active sites, effectively enhancing the adsorption and reaction processes of reactant molecules. In addition, the catalyst has good durability and catalytic stability, which provides a possibility for the future application of electrocatalytic ammonia production.

Comparative Analysis of Gut Microbiomes in Laboratory Chinchillas, Ferrets, and Marmots: Implications for Pathogen Infection Research.

Gut microbes play a vital role in the health and disease of animals, especially in relation to pathogen infections. Chinchillas, ferrets, and marmots are commonly used as important laboratory animals for infectious disease research. Here, we studied the bacterial and fungal microbiota and discovered that chinchillas had higher alpha diversity and a higher abundance of bacteria compared to marmots and ferrets by using the metabarcoding of 16S rRNA genes and ITS2, coupled with co-occurrence network analysis. The dominant microbes varied significantly among the three animal species, particularly in the gut mycobiota. In the ferrets, the feces were dominated by yeast such as Rhodotorula and Kurtzmaniella, while in the chinchillas, we found Teunomyces and Penicillium dominating, and Acaulium, Piromyces, and Kernia in the marmots. Nevertheless, the dominant bacterial genera shared some similarities, such as Clostridium and Pseudomonas across the three animal species. However, there were significant differences observed, such as Vagococcus and Ignatzschineria in the ferrets, Acinetobacter and Bacteroides in the chinchillas, and Bacteroides and Cellvibrio in the marmots. Additionally, our differential analysis revealed significant differences in classification levels among the three different animal species, as well as variations in feeding habitats that resulted in distinct contributions from the host microbiome. Therefore, our data are valuable for monitoring and evaluating the impacts of the microbiome, as well as considering potential applications.

Differential Brain Activation for Four Emotions in VR-2D and VR-3D Modes.

Similar to traditional imaging, virtual reality (VR) imagery encompasses nonstereoscopic (VR-2D) and stereoscopic (VR-3D) modes. Currently, Russell's emotional model has been extensively studied in traditional 2D and VR-3D modes, but there is limited comparative research between VR-2D and VR-3D modes. In this study, we investigate whether Russell's emotional model exhibits stronger brain activation states in VR-3D mode compared to VR-2D mode. By designing an experiment covering four emotional categories (high arousal-high pleasure (HAHV), high arousal-low pleasure (HALV), low arousal-low pleasure (LALV), and low arousal-high pleasure (LAHV)), EEG signals were collected from 30 healthy undergraduate and graduate students while watching videos in both VR modes. Initially, power spectral density (PSD) computations revealed distinct brain activation patterns in different emotional states across the two modes, with VR-3D videos inducing significantly higher brainwave energy, primarily in the frontal, temporal, and occipital regions. Subsequently, Differential entropy (DE) feature sets, selected via a dual ten-fold cross-validation Support Vector Machine (SVM) classifier, demonstrate satisfactory classification accuracy, particularly superior in the VR-3D mode. The paper subsequently presents a deep learning-based EEG emotion recognition framework, adeptly utilizing the frequency, spatial, and temporal information of EEG data to improve recognition accuracy. The contribution of each individual feature to the prediction probabilities is discussed through machine-learning interpretability based on Shapley values. The study reveals notable differences in brain activation states for identical emotions between the two modes, with VR-3D mode showing more pronounced activation.

Impact of typhoon events on microplastic distribution in offshore sediments in Leizhou Peninsula of the South China Sea.

Microplastic is an emerging pollutant and a technical fossil in Anthropocene sediments. Typhoon frequency and intensity have increased due to climate change, which has a major effect on the distribution patterns of microplastics. It is still unknown, though, how the topography of the peninsula affects the reconstruction of the distribution of microplastic in typhoons. Due to frequent typhoons, the Leizhou Peninsula (LZP) in the north part of the South China Sea is an ideal place to study the impact of topographic variations on microplastic distribution during typhoon events. This study investigated microplastics ranging in size from 50 µm to 5 mm in sediment. Microscopic inspection and µ-FTIR tests were used to identify microplastic characteristics from offshore surface sediments before and after typhoons. The average microplastic abundance in offshore sediments decreased from 18 ± 17 items/kg to 15 ± 15 items/kg after typhoons. Results show that typhoons only increase the microplastic abundance in topographically protected areas along the northeast coast of LZP, with no significant difference observed in other regions. The influence of typhoon on the morphological characteristics of microplastics in sediments is more pronounced and widespread, as evidenced by a shift in the predominant shape of microplastics from fibers to fragments and a decrease in size accompanied by an increased abundance within the 100 µm-1 mm fraction. The color of microplastics remained similar before and after typhoons, and the polymer composition of microplastics became more uniform. The alteration of microplastic morphology may be attributed to the enhancement of wave intensity induced by typhoons. This study enhances the comprehension of typhoon-induced impacts on pollutant redistribution, specifically microplastics, thereby providing essential empirical evidence and theoretical foundations for pollution regulation.

Enhanced Interstitial Fluid Extraction and Rapid Analysis via Vacuum Tube-Integrated Microneedle Array Device.

Advancing the development of point-of-care testing (POCT) sensors that utilize interstitial fluid (ISF) presents considerable obstacles in terms of rapid sampling and analysis. Herein, an innovative strategy is introduced that involves the use of a 3D-printed, hollow microneedle array patch (MAP), in tandem with a vacuum tube (VT) connected through a hose, to improve ISF extraction efficiency and facilitate expedited analysis. The employment of negative pressure by the VT allows the MAP device to effectively gather ≈18 µL of ISF from the dermis of a live rabbit ear within a concise period of 5 min. This methodology enables the immediate and minimally invasive measurement of glucose levels within the body, employing personal healthcare meters for quantification. The fusion of the VT and MAP technologies provides for their effortless integration into a comprehensive and mobile system for ISF analysis, accomplished by preloading the hose with custom sensing papers designed to detect specific analytes. Moreover, the design and functionality of this integrated VT-MAP system are intuitively user-friendly, eliminating the requirement for specialized medical expertise. This feature enhances its potential to make a significant impact on the field of decentralized personal healthcare.

The glass phase in the grain boundary of Na3Zr2Si2PO12, created by gallium modulation.

Na3Zr2Si2PO12 has been proven to be a promising electrolyte for solid-state sodium batteries. However, its poor conductivity prevents application, caused by the large ionic resistance created by the grain boundary. Herein, we propose an additional glass phase (Na-Ga-Si-P-O phase) to connect the grain boundary via Ga ion introduction, resulting in enhanced sodium-ion conduction and electrochemical performance. The optimized Na3Zr2Si2PO12-0.15Ga electrolyte exhibits Na+ conductivity of 1.65 mS cm-1 at room temperature and a low activation energy of 0.16 eV, with 20% newly formed glass phase enclosing the grain boundary. Temperature-dependent NMR line shapes and spin-lattice relaxation were used to estimate the Na self-diffusion and Na ion hopping. The dense glass-ceramic electrolyte design strategy and the structure-dynamics-property correlation from NMR, can be extended to the optimization of other materials.

Mining human periodic behaviors via tensor factorization and entropy.

Understanding human periodic behaviors is crucial in many applications. Existing research has shown the existence of periodicity in human behaviors, but has achieved limited success in leveraging location periodicity and obtaining satisfactory accuracy for oscillations in human periodic behaviors. In this article, we propose the Mobility Intention and Relative Entropy (MIRE) model to address these challenges. We employ tensor decomposition to extract mobility intentions from spatiotemporal datasets, thereby revealing hidden structures in users' historical records. Subsequently, we utilize subsequences associated with the same mobility intention to mine human periodic behaviors. Furthermore, we introduce a novel periodicity detection algorithm based on relative entropy. Our experimental results, conducted on real-world datasets, demonstrate the effectiveness of the MIRE model in accurately uncovering human periodic behaviors. Comparative analysis further reveals that the MIRE model significantly outperforms baseline periodicity detection algorithms.

Central vein sign and trigeminal lesions of multiple sclerosis visualised by 7T MRI.

BACKGROUND: Although trigeminal nerve involvement is a characteristic of multiple sclerosis (MS), its prevalence across studies varies greatly due to MRI resolution and cohort selection bias. The mechanism behind the site specificity of trigeminal nerve injury is still unclear. We aim to determine the prevalence of trigeminal nerve involvement in patients with MS in a consecutive 7T brain MRI cohort. METHODS: This observational cohort originates from an ongoing China National Registry of Neuro-Inflammatory Diseases. Inclusion criteria were the following: age 18 years or older, diagnosis of MS according to the 2017 McDonald criteria and no clinical relapse within the preceding 3 months. Each participant underwent 7T MAGNETOM Terra scanner (Siemens, Erlangen, Germany), using a 32-channel phased array coil at Beijing Tiantan Hospital. T1-weighted magnetisation-prepared rapid acquisition gradient echoes, fluid-attenuated inversion recovery (FLAIR) and fluid and white matter suppression images were used to identify lesions. FLAIR* and T2* weighted images were used to identify central vein sign (CVS) within the trigeminal lesions. RESULTS: 120 patients underwent 7T MRI scans between December 2021 and May 2023. 19/120 (15.8%) patients had a total of 45 trigeminal lesions, of which 11/19 (57.9%) were bilateral. The linear lesions extended along the trigeminal nerve, from the root entry zone (REZ) (57.8%, 26/45) to the pontine-medullary nucleus (42.2%, 19/45). 26.9% (7/26) of the lesions in REZ showed a typical central venous sign. CONCLUSION: In this 7T MRI cohort, the prevalence of trigeminal nerve involvement was 15.8%. Characteristic CVS was detected in 26.9% of lesions in REZ. This suggests an inflammatory demyelination mechanism of trigeminal nerve involvement in MS.

Structural and Na-ion diffusion behavior of O3/P3/P2-type NaNi1/3Mn1/3Fe1/3O2 cathode for Na-ion batteries from first-principles study.

A layered sodium-ion battery cathode, O3/P3/P2-type NaNi1/3Mn1/3Fe1/3O2, has been systematically investigated by first-principles density functional theory to explore the detailed structural and Na-ion diffusion behavior during desodiation. Our results suggest that the (NaO6) spacing is greatest in the P3 phase and lowest in the O3 phase, with the P2 phase exhibiting intermediate spacing. During desodiation, the intermediate stages have a greater (NaO6) spacing than the initial and final stages. The great (NaO6) spacing facilitates the formation of the P3 phase, resulting in the structural evolution of NaxNi1/3Mn1/3Fe1/3O2 from the O3 to the P3 phase at x ≈ 0.59, finally reaching the O3 structure again at x ≈ 0.12. The electronic structure clearly proves that both Ni and Fe are active in O3/P3/P2-type NaxNi1/3Mn1/3Fe1/3O2. Ni2+ is oxidized to Ni3+ as Na content decreases from x = 1 to x = 0.66, then further oxidized to Ni4+ at x = 0.33, and finally, Fe3+ → Fe4+ oxidation occurs at x = 0. In the Na ion diffusion behavior, the order of the barrier is O3 (0.82 eV) > P2 (0.53 eV) > P3 (0.35 eV) at the initial stage, whereas it is O3 (0.53 eV) > P3 (0.21 eV) > P2 (0.16 eV) at a highly desodiated stage. The former can be traced back to the (NaO6) spacing, but the latter is related to the different Na sites. Our results thus provide a factor of the structural evolution and Na ion diffusion barrier by considering (NaO6) width and Na site changes during desodiation.

Clostridium lamae sp. nov., a novel bacterium isolated from the fresh feces of alpaca.

A novel Gram-positive, anaerobic, nonspore-forming, rod-shaped bacterium, designated strain NGMCC 1.200840 T, was isolated from the alpacas fresh feces. The taxonomic position of the novel strain was determined using a polyphasic approach. Phylogenetic analysis based on 16S rRNA gene sequences revealed strain NGMCC 1.200840 T was a member of the genus Clostridium and closely related to Clostridium tertium DSM 2485 T (98.16% sequence similarity). Between strains NGMCC 1.200840 T and C. tertium DSM 2485 T, the average nucleotide identity (ANI) and digital DNA-DNA hybridization (dDDH) were 79.91% and 23.50%, respectively. Genomic DNA G + C content is 28.44 mol%. The strain can utilise D-glucose, D-mannitol, D-lactose, D-saccharose, D-maltose, D-xylose, L-arabinose, D-cellobiose, D-mannose, D-melezitose, D-raffinose, D-sorbitol, L-rhamnose, D-trehalose, D-galactose and Arbutin to produce acid. The optimal growth pH was 7, the temperature was 37 °C, and the salt concentration was 0-0.5% (w/v). The major cellular fatty acids (> 10%) included iso-C15:0, anteiso-C15:0 and iso-C17:0 3-OH. The polar lipids consisted of diphosphatidylglycerol, phosphatidylglycerol, phosphatidylethanolamine, three unidentified phospholipids and two unidentified aminolipids. Based on phenotypic, phylogenetic and chemotaxonomic characteristics, NGMCC 1.200840 T represents a novel species within the genus Clostridium, for which the named Clostridium lamae sp. nov. is proposed. The type strain is NGMCC 1.200840 T (= CGMCC 1.18014 T = JCM 35704 T).

NatD epigenetically activates FOXA2 expression to promote breast cancer progression by facilitating MMP14 expression.

N-α-acetyltransferase D (NatD) mediates N-α-terminal acetylation of histone H4 (Nt-Ac-H4), but its role in breast cancer metastasis remains unknown. Here, we show that depletion of NatD directly represses the expression of FOXA2, and is accompanied by a significant reduction in Nt-Ac-H4 enrichment at the FOXA2 promoter. We show that NatD is commonly upregulated in primary breast cancer tissues, where its expression level correlates with FOXA2 expression, enhanced invasiveness, and poor clinical outcomes. Furthermore, we show that FOXA2 promotes the migration and invasion of breast cancer cells by activating MMP14 expression. MMP14 is also upregulated in breast cancer tissues, where its expression level correlates with FOXA2 expression and poor clinical prognosis. Our study shows that the NatD-FOXA2-MMP14 axis functions as a key signaling pathway to promote the migratory and invasive capabilities of breast cancer cells, suggesting that NatD is a critical epigenetic modulator of cell invasion during breast cancer progression.

Deep learning and machine learning predictive models for neurological function after interventional embolization of intracranial aneurysms.

Objective: The objective of this study is to develop a model to predicts the postoperative Hunt-Hess grade in patients with intracranial aneurysms by integrating radiomics and deep learning technologies, using preoperative CTA imaging data. Thereby assisting clinical decision-making and improving the assessment and prognosis of postoperative neurological function. Methods: This retrospective study encompassed 101 patients who underwent aneurysm embolization surgery. 851 radiomic features were extracted from CTA images. 512 deep learning features are extracted from last layer of ResNet50 deep convolutional neural network model. The feature screening process pipeline encompassed intraclass correlation coefficient analysis, principal component analysis, U test, spearman correlation analysis, minimum redundancy maximum relevance algorithm and Lasso regression, to identify features most correlated with postoperative Hunt-Hess grading. In the model construction phase, three distinct models were constructed: radiomics feature-based model (RSM), deep learning feature-based model (DLM), and deep learning-radiomics feature fusion model (DLRSCM). The study also calculated the radiomics score and combined it with clinical data to construct a Nomogram for predictive modeling. DLM, RSM and DLRSCM model was constructed by 9 base algorithms and 1 ensemble learning algorithm - Stacking ensemble model. Model performance was evaluated based on the area under the Receiver Operating Characteristic (ROC) curve (AUC), Matthews Correlation Coefficient (MCC), calibration curves, and decision curves analysis. Results: 5 significant radiomic feature and 4 significant deep learning features were obtained through the feature selection process. These features were utilized for model construction. Bootstrap resampling method was used for internal validation of the models. In terms of model evaluation, the DLM model, the stacking ensemble algorithm results achieved an AUC of 0.959 and MCC of 0.815. In the RSM model, the stacking ensemble model AUC was 0.935 and MCC was 0.793. The stacking ensemble model in DLRSCM outperformed others, with an AUC of 0.968 and MCC of 0.820. Results indicated that the ANN performed optimally among all base models, while the stacked ensemble learning model exhibited the highest predictive performance. Conclusion: This study demonstrates that the combination of radiomics and deep learning is an effective approach to predict the postoperative Hunt-Hess grade in patients with intracranial aneurysms. This holds significant value in the early identification of postoperative neurological complications and in enhancing clinical decision-making.

Molecular map of disulfidptosis-related genes in lung adenocarcinoma: the perspective toward immune microenvironment and prognosis.

BACKGROUND: Disulfidptosis is a recently discovered form of programmed cell death that could impact cancer development. Nevertheless, the prognostic significance of disulfidptosis-related genes (DRGs) in lung adenocarcinoma (LUAD) requires further clarification. METHODS: This study systematically explores the genetic and transcriptional variability, prognostic relevance, and expression profiles of DRGs. Clusters related to disulfidptosis were identified through consensus clustering. We used single-sample gene set enrichment analysis and ESTIMATE to assess the tumor microenvironment (TME) in different subgroups. We conducted a functional analysis of differentially expressed genes between subgroups, which involved gene ontology, the Kyoto encyclopedia of genes and genomes, and gene set variation analysis, in order to elucidate their functional status. Prognostic risk models were developed using univariate Cox regression and the least absolute shrinkage and selection operator regression. Additionally, single-cell clustering and cell communication analysis were conducted to enhance the understanding of the importance of signature genes. Lastly, qRT-PCR was employed to validate the prognostic model. RESULTS: Two clearly defined DRG clusters were identified through a consensus-based, unsupervised clustering analysis. Observations were made concerning the correlation between changes in multilayer DRG and various clinical characteristics, prognosis, and the infiltration of TME cells. A well-executed risk assessment model, known as the DRG score, was developed to predict the prognosis of LUAD patients. A high DRG score indicates increased TME cell infiltration, a higher mutation burden, elevated TME scores, and a poorer prognosis. Additionally, the DRG score showed a significant correlation with the tumor mutation burden score and the tumor immune dysfunction and exclusion score. Subsequently, a nomogram was established for facilitating the clinical application of the DRG score, showing good predictive ability and calibration. Additionally, crucial DRGs were further validated by single-cell sequencing data. Finally, crucial DRGs were further validated by qRT-PCR and immunohistochemistry. CONCLUSION: Our new DRG signature risk score can predict the immune landscape and prognosis of LUAD. It also serves as a reference for LUAD's immunotherapy and chemotherapy.