Progesterone improved the behavior of PC12 cells under OGD/R by reducing FABP5 expression and inhibiting TLR4/NF-κB signaling pathway.

Herein, PC12 cells were applied to detect the impact of progesterone under oxygen glucose deprivation/reperfusion (OGD/R) stimulation. The cell proliferation of PC12 cells was evaluated by cell counting kit-8 assay, and the concentrations of MDA, ROS and SOD were examined by their corresponding Enzyme Linked Immunosorbent Assay kits. The invasion and migration properties of PC12 cells were evaluated by transwell and wound healing assays, respectively. The expression patterns of related genes were evaluated by western blot and qPCR. Under OGD/R stimulation, progesterone treatment could elevate the viability of PC12 cells, reduce the levels of MDA and ROS, and elevate the concentration of SOD. Moreover, progesterone treatment could strengthen the invasion and migration abilities of PC12 cells under OGD/R condition, as well as decrease the apoptosis and inflammation. FABP5 expression was significantly increased in PC12 cells under OGD/R stimulation, which was reversed after progesterone stimulation. Under OGD/R stimulation, the protective effects of progesterone on PC12 cells were strengthened after si-FABP5 treatment. The protein levels of TLR4, p-P65 NF-κB, and P65 NF-κB in OGD/R-induced PC12 cells were increased, which were inhibited after progesterone treatment. Progesterone exerted protective effects on PC12 cells by targeting FABP5 under OGD/R stimulation.

Inferring a directed acyclic graph of phenotypes from GWAS summary statistics.

Estimating phenotype networks is a growing field in computational biology. It deepens the understanding of disease etiology and is useful in many applications. In this study, we present a method that constructs a phenotype network by assuming a Gaussian linear structure model embedding a directed acyclic graph (DAG). We utilize genetic variants as instrumental variables and show how our method only requires access to summary statistics from a genome-wide association study (GWAS) and a reference panel of genotype data. Besides estimation, a distinct feature of the method is its summary statistics-based likelihood ratio test on directed edges. We applied our method to estimate a causal network of 29 cardiovascular-related proteins and linked the estimated network to Alzheimer's disease (AD). A simulation study was conducted to demonstrate the effectiveness of this method. An R package sumdag implementing the proposed method, all relevant code, and a Shiny application are available.

Enhanced Light Absorption and Elevated Viscosity of Atmospheric Brown Carbon through Evaporation of Volatile Components.

Samples of brown carbon (BrC) material were collected from smoke emissions originating from wood pyrolysis experiments, serving as a proxy for BrC representative of biomass burning emissions. The acquired samples, referred to as "pyrolysis oil (PO1)," underwent subsequent processing by thermal evaporation of their volatile compounds, resulting in a set of three additional samples with volume reduction factors of 1.33, 2, and 3, denoted as PO1.33, PO2, and PO3. The chemical compositions of these POx samples and their BrC chromophore features were analyzed using a high-performance liquid chromatography instrument coupled with a photodiode array detector and a high-resolution mass spectrometer. The investigation revealed a noteworthy twofold enhancement of BrC light absorption observed for the progression of PO1 to PO3 samples, assessed across the spectral range of 300-500 nm. Concurrently, a decrease in the absorption Ångstrom exponent (AAE) from 11 to 7 was observed, indicating a weaker spectral dependence. The relative enhancement of BrC absorption at longer wavelengths was more significant, as exemplified by the increased mass absorption coefficient (MAC) measured at 405 nm from 0.1 to 0.5 m2/g. Molecular characterization further supports this darkening trend, manifesting as a depletion of small oxygenated, less absorbing monoaromatic compounds and the retention of relatively large, less polar, more absorbing constituents. Noteworthy alterations of the PO1 to PO3 mixtures included a reduction in the saturation vapor pressure of their components and an increase in viscosity. These changes were quantified by the mean values shifting from approximately 1.8 × 103 µg/m3 to 2.3 µg/m3 and from ∼103 Pa·s to ∼106 Pa·s, respectively. These results provide quantitative insights into the extent of BrC aerosol darkening during atmospheric aging through nonreactive evaporation. This new understanding will inform the refinement of atmospheric and chemical transport models.

Unveiling the Molecular Characteristics, Origins, and Formation Mechanism of Reduced Nitrogen Organic Compounds in the Urban Atmosphere of Shanghai Using a Versatile Aerosol Concentration Enrichment System.

Reduced nitrogen-containing organic compounds (NOCs) in aerosols play a crucial role in altering their light-absorption properties, thereby impacting regional haze and climate. Due to the low concentration levels of individual NOCs in the air, the utilization of accurate detection and quantification technologies becomes essential. For the first time, this study investigated the diurnal variation, chemical characteristics, and potential formation pathways of NOCs in urban ambient aerosols in Shanghai using a versatile aerosol concentration enrichment system (VACES) coupled with HPLC-Q-TOF-MS. The results showed that NOCs accounted over 60% of identified components of urban organic aerosols, with O/N < 3 compounds being the major contributors (>70%). The predominance of the positive ionization mode suggested the prevalence of reduced NOCs. Higher relative intensities and number fractions of NOCs were observed during nighttime, while CHO compounds showed an opposite trend. Notably, a positive correlation between the intensity of NOCs and ammonium during the nighttime was observed, suggesting that the reaction of ammonium to form imines may be a potential pathway for the formation of reduced NOCs during the nighttime. Seven prevalent types of reduced NOCs in autumn and winter were identified and characterized by an enrichment of CH2 long-chain homologues. These NOCs included alkyl, cyclic, and aromatic amides in CHON compounds, as well as heterocyclic or cyclic amines and aniline homologue series in CHN compounds, which were associated with anthropogenic activities and may be capable of forming light-absorbing chromophores or posing harm to human health. The findings highlight the significant contributions of both primary emissions and ammonium chemistry, particularly amination processes, to the pollution of reduced NOCs in Shanghai's atmosphere.

Diverse Metabolic Effects of Cooking Oil Fume from Four Edible Oils on Human BEAS-2B Cells: Implications for Health Guidelines.

The 2021 WHO guidelines stress the importance of measuring ultrafine particles using particle number concentration (PNC) for health assessments. However, commonly used particle metrics such as aerodynamic diameter and number concentrations do not fully capture the diverse chemical makeup of complex particles. To address this issue, our study used high-throughput mass spectrometry to analyze the properties of cooking oil fumes (COFs) in real time and evaluate their impact on BEAS-2B cell metabolism. Results showed insignificant differences in COF number size distributions between soybean oil and olive oil (peak concentrations of 5.20 × 105/cm3), as well as between corn oil and peanut oil (peak concentrations of 4.35 × 105/cm3). Despite the similar major chemical components among the four COFs, variations in metabolic damage were observed, indicating that the relatively small amount of chemical components of COFs can also influence particle behavior within the respiratory system, thereby impacting biological responses. Additionally, interactions between accompanying gaseous COFs and particles may alter their chemical composition through various mechanisms, introducing additional chemicals and modifying existing proportions. Hence, the chemical composition and gaseous components of COFs hold equal importance to the particle number concentration (PNC) when assessing their impact on human health. The absence of these considerations in the current guidelines underscores a research gap. It is imperative to acknowledge that for a more comprehensive approach to safeguarding public health, guidelines must be regularly updated to reflect new scientific findings and robust epidemiological evidence.

Quantification and Characterization of Fine Plastic Particles as Considerable Components in Atmospheric Fine Particles.

The negative effects of air pollution, especially fine particulate matter (PM2.5, particles with an aerodynamic diameter of ≤2.5 µm), on human health, climate, and ecosystems are causing significant concern. Nevertheless, little is known about the contributions of emerging pollutants such as plastic particles to PM2.5 due to the lack of continuous measurements and characterization methods for atmospheric plastic particles. Here, we investigated the levels of fine plastic particles (FPPs) in PM2.5 collected in urban Shanghai at a 2 h resolution by using a novel versatile aerosol concentration enrichment system that concentrates ambient aerosols up to 10-fold. The FPPs were analyzed offline using the combination of spectroscopic and microscopic techniques that distinguished FPPs from other carbon-containing particles. The average FPP concentrations of 5.6 µg/m3 were observed, and the ratio of FPPs to PM2.5 was 13.2% in this study. The FPP sources were closely related to anthropogenic activities, which pose a potential threat to ecosystems and human health. Given the dramatic increase in plastic production over the past 70 years, this study calls for better quantification and control of FPP pollution in the atmosphere.

Soil bacterial community diversity and life strategy during slope restoration on an uninhabited island: changes under the aggregate spray-seeding technique.

AIMS: We investigated the effects of the aggregate spray-seeding (ASS) technique on soil bacterial community diversity, life strategies, and seasonal change. METHODS AND RESULTS: Soil from six plots with original vegetation (CK, n = 6) was compared to soil from 15 plots with spray-seeding restoration (SR, n = 15) using environmental DNA sequencing. The bacterial Shannon and Chao1 indices of SR soils were significantly greater (P < 0.05) than those of CK soils. The Chao1 index for the SR soil bacterial community was significantly greater in summer (P < 0.05) than in winter. The ratio of the relative abundance of bacterial K-strategists to r-strategists (K/r) and the DNA guanine-cytosine (GC) content in the SR soil were significantly lower (P < 0.05) than those in the CK soil. Principal coordinate analysis revealed significant differences between the SR and CK bacterial communities. The GC content was positively correlated with the K/r ratio. Soil conductivity was negatively associated with the K/r ratio and GC content, indicating that ionic nutrients were closely related to bacterial life strategies. CONCLUSIONS: The ASS technique improved soil bacterial diversity, altered community composition, and favored bacterial r-strategists.

Left frontal eye field encodes sound locations during passive listening.

Previous studies reported that auditory cortices (AC) were mostly activated by sounds coming from the contralateral hemifield. As a result, sound locations could be encoded by integrating opposite activations from both sides of AC ("opponent hemifield coding"). However, human auditory "where" pathway also includes a series of parietal and prefrontal regions. It was unknown how sound locations were represented in those high-level regions during passive listening. Here, we investigated the neural representation of sound locations in high-level regions by voxel-level tuning analysis, regions-of-interest-level (ROI-level) laterality analysis, and ROI-level multivariate pattern analysis. Functional magnetic resonance imaging data were collected while participants listened passively to sounds from various horizontal locations. We found that opponent hemifield coding of sound locations not only existed in AC, but also spanned over intraparietal sulcus, superior parietal lobule, and frontal eye field (FEF). Furthermore, multivariate pattern representation of sound locations in both hemifields could be observed in left AC, right AC, and left FEF. Overall, our results demonstrate that left FEF, a high-level region along the auditory "where" pathway, encodes sound locations during passive listening in two ways: a univariate opponent hemifield activation representation and a multivariate full-field activation pattern representation.

Age-adjusted Charlson comorbidity index is associated with the risk of osteoporosis in older fall-prone men: a retrospective cohort study.

BACKGROUND: There is growing evidence linking the age-adjusted Charlson comorbidity index (aCCI), an assessment tool for multimorbidity, to fragility fracture and fracture-related postoperative complications. However, the role of multimorbidity in osteoporosis has not yet been thoroughly evaluated. We aimed to investigate the association between aCCI and the risk of osteoporosis in older adults at moderate to high risk of falling. METHODS: A total of 947 men were included from January 2015 to August 2022 in a hospital in Beijing, China. The aCCI was calculated by counting age and each comorbidity according to their weighted scores, and the participants were stratified into two groups by aCCI: low (aCCI < 5), and high (aCCI ≥5). The Kaplan Meier method was used to assess the cumulative incidence of osteoporosis by different levels of aCCI. The Cox proportional hazards regression model was used to estimate the association of aCCI with the risk of osteoporosis. Receiver operating characteristic (ROC) curve was adapted to assess the performance for aCCI in osteoporosis screening. RESULTS: At baseline, the mean age of all patients was 75.7 years, the mean BMI was 24.8 kg/m2, and 531 (56.1%) patients had high aCCI while 416 (43.9%) were having low aCCI. During a median follow-up of 6.6 years, 296 participants developed osteoporosis. Kaplan-Meier survival curves showed that participants with high aCCI had significantly higher cumulative incidence of osteoporosis compared with those had low aCCI (log-rank test: P < 0.001). When aCCI was examined as a continuous variable, the multivariable-adjusted model showed that the osteoporosis risk increased by 12.1% (HR = 1.121, 95% CI 1.041-1.206, P = 0.002) as aCCI increased by one unit. When aCCI was changed to a categorical variable, the multivariable-adjusted hazard ratios associated with different levels of aCCI [low (reference group) and high] were 1.00 and 1.557 (95% CI 1.223-1.983) for osteoporosis (P <  0.001), respectively. The aCCI (cutoff ≥5) revealed an area under ROC curve (AUC) of 0.566 (95%CI 0.527-0.605, P = 0.001) in identifying osteoporosis in older fall-prone men, with sensitivity of 64.9% and specificity of 47.9%. CONCLUSIONS: The current study indicated an association of higher aCCI with an increased risk of osteoporosis among older fall-prone men, supporting the possibility of aCCI as a marker of long-term skeletal-related adverse clinical outcomes.

The effect of mood on shaping belief and recollection following false feedback.

The current study examined how mood affects the impact of false feedback on belief and recollection. In a three-session experiment, participants first watched 40 neutral mini videos, which were accompanied by music to induce either a positive or negative mood, or no music. Following a recognition test, they received false feedback to reduce belief in the occurrence of the events displayed in some of the videos (Session 2). This was followed by an immediate memory test and a delayed memory assessment one week later (Session 3). The results revealed that participants in negative mood reported higher belief scores compared to those in positive moods, despite an overall decline in belief scores for all groups following the false feedback. Notably, individuals in negative moods exhibited less reduction in their belief scores after encountering challenges, thereby maintaining a higher accuracy in their testimonies. Over time, a reduction in the clarity of participants' memory recall was observed, which correspondingly reduced their testimony accuracy. This study thus indicates that mood states play a role in shaping belief and memory recall under the influence of false feedback.

Inducing emotionally negative nonbelieved memories using negative pictures.

Memories that can be recalled but are no longer believed are termed nonbelieved memories. The current studies examined the creation of emotionally negative nonbelieved memories after viewing negatively valenced pictures. In both experiments, participants took part in two sessions. In Session 1, after being presented with a set of neutral and negative pictures, participants had to rate their emotional state. One week later, in Session 2, participants had to complete a recognition task to identify pictures that had appeared during the previous session. During this task, participants' memories for some pictures were challenged by telling them that their answers were incorrect in order to evoke nonbelieved memories. The experimental procedure was successful in creating nonbelieved memories in the participants. Specifically, in Experiment 1 (N = 35), we induced nonbelieved true memories for both negative and neutral pictures. We found a significant decrease in both belief and recollection after the challenge, with the change in belief being twice as large as the change in recollection. In Experiment 2 (N = 43), we successfully induced both nonbelieved true and false memories for negative pictures. Again, the reduction of belief was significantly greater than that of recollection. In general, participants evinced better memory for negative pictures, but following challenges people were just as likely to accept false social feedback and change their memories regarding other types of pictures. In both experiments, our challenges did not lead to notable changes in emotional state. In general, our findings show that emotionally negative nonbelieved memories can be successfully evoked in an experimental setting.

Retracted memories in the general population: are there differences between eastern and western countries?

The main purpose of the current studies was to examine retracted experiences in the general population from various cultural backgrounds. More specifically, in two studies, we examined the details of memory retraction experiences, the reasons for retraction, and the outcomes of retraction in participants from China and other countries, mainly the United States of America. It was found that memory retraction experiences appeared to be quite common. In the sample of Chinese participants (Study 1: N = 1380), 50.58% reported at least one such an experience, whereas in respondents from other countries (Study 2; N = 425), a significantly lower but still substantial prevalence rate of 35% was found. In general, the retracted memories predominantly involved positive events and some respondents experienced pressure during the withdrawal. Social feedback and event plausibility were the two main reasons for the withdrawal. Compared to recollection scores, belief scores decreased significantly after withdrawal, and some respondents even formed nonbelieved memories. After retracting the memories, most respondents felt they gained benefits (e.g., they had resolved a psychological problem that had bothered them for years). These studies give us a more general understanding of retracted memory experiences in the general population.

Development and internal validation of a clinical prediction model for osteopenia in Chinese middle-aged and elderly men: a prospective cohort study.

BACKGROUND: Early identification of patients at risk of osteopenia is an essential step in reducing the population at risk for fractures. We aimed to develop and validate a prediction model for osteopenia in Chinese middle-aged and elderly men that provides individualized risk estimates. METHODS: In this prospective cohort study, 1109 patients who attend regular physical examinations in the Second Medical Centre of Chinese PLA General Hospital were enrolled from 2015.03 to 2015.09. The baseline risk factors included dietary habits, exercise habits, medical histories and medication records. Osteopenia during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Internal validation was conducted using bootstrapping to correct the optimism. The independent sample T-test analysis, Mann_Whitney U test, Chi-Square Test and multivariable Cox regression analysis were utilized to identify predictive factors for osteopenia in Chinese middle-aged and elderly men. A nomogram based on the seven variables was built for clinical use. Concordance index (C-index), receiver operating characteristic curve (ROC), decision curve analysis (DCA) and calibration curve were used to evaluate the efficiency of the nomogram. RESULTS: The risk factors included in the prediction model were bone mineral density at left femoral neck (LNBMD), hemoglobin (Hb), serum albumin (ALB), postprandial blood glucose (PBG), fatty liver disease (FLD), smoking and tea consumption. The C-index for the risk nomogram was 0.773 in the prediction model, which presented good refinement. The AUC of the risk nomogram at different time points ranged from 0.785 to 0.817, exhibiting good predictive ability and performance. In addition, the DCA showed that the nomogram had a good clinical application value. The nomogram calibration curve indicated that the prediction model was consistent. CONCLUSIONS: Our study provides a novel nomogram and a web calculator that can effectively predict the 7-year incidence risk of osteopenia in Chinese middle-aged and elderly men. It is convenient for clinicians to prevent fragility fractures in the male population.

Functional traits explain waterbirds' host status, subtype richness, and community-level infection risk for avian influenza.

Species functional traits can influence pathogen transmission processes, and consequently affect species' host status, pathogen diversity, and community-level infection risk. We here investigated, for 143 European waterbird species, effects of functional traits on host status and pathogen diversity (subtype richness) for avian influenza virus at species level. We then explored the association between functional diversity and HPAI H5Nx occurrence at the community level for 2016/17 and 2021/22 epidemics in Europe. We found that both host status and subtype richness were shaped by several traits, such as diet guild and dispersal ability, and that the community-weighted means of these traits were also correlated with community-level risk of H5Nx occurrence. Moreover, functional divergence was negatively associated with H5Nx occurrence, indicating that functional diversity can reduce infection risk. Our findings highlight the value of integrating trait-based ecology into the framework of diversity-disease relationship, and provide new insights for HPAI prediction and prevention.

Food patch use of Japanese quail (Coturnix japonica) varies with personality traits.

BACKGROUND: The classic optimal foraging theory (OFT) predicts animals' food patch use assuming that individuals in a population use the same strategy while foraging. However, due to the existence of animal personality, i.e. repeatable inter-individual differences and intra-individual consistency in behaviours over time and/or across contexts, individuals often exhibit different behavioural strategies, challenging the basic assumptions of the OFT. Here, we tested whether personality traits (boldness and exploration in open arena) of Japanese quail (Coturnix japonica, 38 females and 34 males) influenced their patch use in two foraging experiments with different inter-patch distances (i.e. 2 m in Experiment 1 and 3 m in Experiment 2). RESULTS: The total feeding time and food intake of individuals did not differ between Experiment 1 and 2, but in both experiments, proactive (i.e. bolder and more explorative) individuals had longer feeding time and higher food intake than reactive individuals. In Experiment 1, proactive quails changed patches more frequently and had shorter mean patch residence time than reactive individuals, while the effects were not significant in Experiment 2. The quails reduced patch residence time along with feeding, and this trend was weakened in Experiment 2 which had longer inter-patch distance. CONCLUSIONS: The above results suggest that personality traits affect animals' patch use, while the effects might be weakened with longer inter-patch distance. Our study highlights that animal personality should be considered when investigating animals' foraging behaviours because individuals may not adopt the same strategy as previously assumed. Furthermore, the interaction between personality traits and inter-patch distances, which is related to movement cost and capacity of information gathering, should also be considered.

Well-being is associated with cortical thickness network topology of human brain.

BACKGROUND: Living a happy and meaningful life is an eternal topic in positive psychology, which is crucial for individuals' physical and mental health as well as social functioning. Well-being can be subdivided into pleasure attainment related hedonic well-being or emotional well-being, and self-actualization related eudaimonic well-being or psychological well-being plus social well-being. Previous studies have mostly focused on human brain morphological and functional mechanisms underlying different dimensions of well-being, but no study explored brain network mechanisms of well-being, especially in terms of topological properties of human brain morphological similarity network. METHODS: Therefore, in the study, we collected 65 datasets including magnetic resonance imaging (MRI) and well-being data, and constructed human brain morphological network based on morphological distribution similarity of cortical thickness to explore the correlations between topological properties including network efficiency and centrality and different dimensions of well-being. RESULTS: We found emotional well-being was negatively correlated with betweenness centrality in the visual network but positively correlated with eigenvector centrality in the precentral sulcus, while the total score of well-being was positively correlated with local efficiency in the posterior cingulate cortex of cortical thickness network. CONCLUSIONS: Our findings demonstrated that different dimensions of well-being corresponded to different cortical hierarchies: hedonic well-being was involved in more preliminary cognitive processing stages including perceptual and attentional information processing, while hedonic and eudaimonic well-being might share common morphological similarity network mechanisms in the subsequent advanced cognitive processing stages.

Application research of AI-assisted compressed sensing technology in MRI scanning of the knee joint: 3D-MRI perspective.

OBJECTIVE: To investigate the potential applicability of AI-assisted compressed sensing (ACS) in knee MRI to enhance and optimize the scanning process. METHODS: Volunteers and patients with sports-related injuries underwent prospective MRI scans with a range of acceleration techniques. The volunteers were subjected to varied ACS acceleration levels to ascertain the most effective level. Patients underwent scans at the determined optimal 3D-ACS acceleration level, and 3D compressed sensing (CS) and 2D parallel acquisition technology (PAT) scans were performed. The resultant 3D-ACS images underwent 3.5 mm/2.0 mm multiplanar reconstruction (MPR). Experienced radiologists evaluated and compared the quality of images obtained by 3D-ACS-MRI and 3D-CS-MRI, 3.5 mm/2.0 mm MPR and 2D-PAT-MRI, diagnosed diseases, and compared the results with the arthroscopic findings. The diagnostic agreement was evaluated using Cohen's kappa correlation coefficient, and both absolute and relative evaluation methods were utilized for objective assessment. RESULTS: The study involved 15 volunteers and 53 patients. An acceleration factor of 10.69 × was identified as optimal. The quality evaluation showed that 3D-ACS provided poorer bone structure visualization, and improved cartilage visualization and less satisfactory axial images with 3.5 mm/2.0 mm MPR than 2D-PAT. In terms of objective evaluation, the relative evaluation yielded satisfactory results across different groups, while the absolute evaluation revealed significant variances in most features. Nevertheless, high levels of diagnostic agreement (κ: 0.81-0.94) and accuracy (0.83-0.98) were observed across all diagnoses. CONCLUSION: ACS technology presents significant potential as a replacement for traditional CS in 3D-MRI knee scans, allowing thinner MPRs and markedly faster scans without sacrificing diagnostic accuracy. CLINICAL RELEVANCE STATEMENT: 3D-ACS-MRI of the knee can be completed in the 160 s with good diagnostic consistency and image quality. 3D-MRI-MPR can replace 2D-MRI and reconstruct images with thinner slices, which helps to optimize the current MRI examination process and shorten scanning time. KEY POINTS: • AI-assisted compressed sensing technology can reduce knee MRI scan time by over 50%. • 3D AI-assisted compressed sensing MRI and related multiplanar reconstruction can replace traditional accelerated MRI and yield thinner 2D multiplanar reconstructions. • Successful application of 3D AI-assisted compressed sensing MRI can help optimize the current knee MRI process.

A deep learning framework for intracranial aneurysms automatic segmentation and detection on magnetic resonance T1 images.

OBJECTIVES: To design a deep learning-based framework for automatic segmentation and detection of intracranial aneurysms (IAs) on magnetic resonance T1 images and test the robustness and performance of framework. METHODS: A retrospective diagnostic study was conducted based on 159 IAs from 136 patients who underwent the T1 images. Among them, 127 cases were randomly selected for training and validation, and 32 cases were used to assess the accuracy and consistency of our algorithm. We developed and assembled three convolutional neural networks for the segmentation and detection of IAs. The segmentation and detection performance of the model were compared with the ground truth, and various metrics were calculated at the voxel level, IAs level, and patient level to show the performance of our framework. RESULTS: Our assembled model achieved overall Dice, voxel-level sensitivity, specificity, balanced accuracy, and F1 score of 0.802, 0.874, 0.9998, 0.937, and 0.802, respectively. A coincidence greater than 0.7 between the aneurysms predicted by the model and the ground truth was considered as a true positive. For IAs detection, the sensitivity reached 90.63% with 0.58 false positives per case. The volume of IAs segmented by our model showed a high agreement and consistency with the volume of IAs labeled by experts. CONCLUSION: The deep learning framework is achievable and robust for IAs segmentation and detection. Our model offers more clinical application opportunities compared to digital subtraction angiography (DSA)-based, CTA-based, and MRA-based methods. CLINICAL RELEVANCE STATEMENT: Our deep learning framework effectively detects and segments intracranial aneurysms using clinical routine T1 sequences, showing remarkable effectiveness and offering great potential for improving the detection of latent intracranial aneurysms and enabling early identification. KEY POINTS: •There is no segmentation method based on clinical routine T1 images. Our study shows that the proper deep learning framework can effectively localize the intracranial aneurysms. •The T1-based segmentation and detection method is more universal than other angiography-based detection methods, which can potentially reduce missed diagnoses caused by the absence of angiography images. •The deep learning framework is robust and has the potential to be applied in a clinical setting.

Influence of Polycyclic Aromatic Compounds and Oxidation States of Soot Organics on the Metabolome of Human-Lung Cells (A549): Implications for Vehicle Fuel Selection.

Decades of research have established the toxicity of soot particles resulting from incomplete combustion. However, the unique chemical compounds responsible for adverse health effects have remained uncertain. This study utilized mass spectrometry to analyze the chemical composition of extracted soot organics at three oxidation states, aiming to establish quantitative relationships between potentially toxic chemicals and their impact on human alveolar basal epithelial cells (A549) through metabolomics-based evaluations. Targeted analysis using MS/MS indicated that particles with a medium oxidation state contained the highest total abundance of compounds, particularly oxygen-containing polycyclic aromatic hydrocarbons (OPAHs) composed of fused benzene rings and unsaturated carbonyls, which may cause oxidative stress, characterized by the upregulation of three specific metabolites. Further investigation focused on three specific OPAH standards: 1,4-naphthoquinone, 9-fluorenone, and anthranone. Pathway analysis indicated that exposure to these compounds affected transcriptional functions, the tricarboxylic acid cycle, cell proliferation, and the oxidative stress response. Biodiesel combustion emissions had higher concentrations of PAHs, OPAHs, and nitrogen-containing PAHs (NPAHs) compared with other fuels. Quinones and 9,10-anthraquinone were identified as the dominant compounds within the OPAH category. This knowledge enhances our understanding of the compounds contributing to adverse health effects observed in epidemiological studies and highlights the role of aerosol composition in toxicity.

Spatiotemporal and sensory modality attention processing with domain-specific representations in frontoparietal areas.

The frontoparietal network (FPN), including bilateral frontal eye field, inferior parietal sulcus, and supplementary motor area, has been linked to attention processing, including spatiotemporal and sensory modality domains. However, it is unclear whether FPN encodes representations of these domains that are generalizable across subdomains. We decomposed multivariate patterns of functional magnetic resonance imaging activity from 20 participants into domain-specific components and identified latent multivariate representations that generalized across subdomains. The 30 experimental conditions were organized into unimodal-bimodal and spatial-temporal models. We found that brain areas in the FPN, form the primary network that modulated during attention across domains. However, the activation patterns of areas within the FPN were reorganized according to the specific attentional demand, especially when pay attention to different sensory, suggesting distinct regional neural representations associated with specific attentional processes within FPN. In addition, there were also other domain-specific areas outside the FPN, such as the dorsolateral prefrontal cortex. Our conclusion is that, according to the results of the analysis of representation similarity, 2 types of activated brain regions, related to attention domain detailed information processing and general information processing, can be revealed.