Knowledge, attitudes, and perceptions of influenza vaccine among pregnant women in Minhang District, Shanghai.

This study aimed to assess the attitudes and willingness of pregnant women to receive the influenza vaccine and the factors influencing their decisions. A sample survey was conducted among pregnant women receiving prenatal care at various medical institutions in Minhang District, Shanghai, from March to June 2023. The survey included inquiries about demographic information, knowledge, and perception of influenza disease and influenza vaccine. Logistic regression models and chi-square tests were used to analyze the data. 6.9% (78/1125) of participants considered receiving the influenza vaccine during pregnancy. Participants with graduate education or above (OR = 4.632, 95%CI: 1.046-20.517), non-office workers (OR = 2.784, 95%CI: 1.560-4.970), and participants whose spouses were not office workers (OR = 0.518, 95% CI: 0.294-0.913) were significantly associated with high intent to vaccinate. Participants with superior knowledge (>30 points) exhibited greater willingness (p < .001). Participants who viewed post-influenza symptoms as mild had a significantly lower willingness to vaccinate during pregnancy (2.3%), compared to those who disagreed (p = .015). Conversely, those recognizing a heightened risk of hospitalization due to respiratory diseases in pregnant women post-influenza were significantly more inclined to vaccinate during pregnancy (8.8%) (p = .007). Participants recognizing benefits uniformly expressed willingness to receive the influenza vaccine during pregnancy (p < .001), while those perceiving barriers uniformly rejected vaccination (p < .001). Higher education, non-office worker status, and having an office worker spouse correlate with greater willingness to receive the influenza vaccine during pregnancy. Enhanced knowledge and accurate perceptions of influenza and its vaccine influenced willingness. Accumulating knowledge about influenza and its vaccine fosters accurate perceptions. Notably, overall willingness to vaccinate during pregnancy remains low, likely due to safety concerns, and lack of accurate perceptions. Targeted health education, improved communication between healthcare providers and pregnant women, and campaigns highlighting vaccine benefits for mothers and children are essential.

Antioxidant mechanism, spectroscopic and pharmacological properties of four flavonoids: DFT, docking and molecular dynamics.

Myricetin (1), quercetin (2), kaempferol (3) and kaempferide (4) were flavonoids with phenolic hydroxyl groups. The antioxidant and pharmacological mechanisms of them were investigated in detail. The lowest hydroxyl dissociation enthalpies of 1, 2, 3 and 4 were calculated by DFT, respectively. The hydroxyl dissociation enthalpies of the four flavonoids at the O2 site are the highest. By analyzing the intramolecular hydrogen bonds and HOMO-LUMO orbitals of the four flavonoids, the reasons for their divergence of hydroxyl dissociation enthalpies and antioxidant mechanisms were further investigated. The UV-vis and IR spectra of four flavonoids were compared. The interactions about electrostatic attraction, p-π conjugation and hydrogen bond combined the flavonoid with the target protein closely. The root mean square deviation of peroxisome proliferator-activated receptor γ combined with 1, 2 and 3 increased, while that of PPARγ combined with 4 decreased.

A full-length glycoprotein mRNA vaccine confers complete protection against severe fever with thrombocytopenia syndrome virus, with broad-spectrum protective effects against bandaviruses.

Highly pathogenic viruses from family Phenuiviridae, which are mainly transmitted by arthropods, have intermittently sparked epidemics worldwide. In particular, tick-borne bandaviruses, such as severe fever with thrombocytopenia syndrome virus (SFTSV), continue to spread in mountainous areas, resulting in an average mortality rate as high as 10.5%, highlighting the urgency and importance of vaccine development. Here, an mRNA vaccine developed based on the full-length SFTSV glycoprotein, containing both the receptor-binding domain and the fusion domain, was shown to confer complete protection against SFTSV at a very low dose by triggering a type 1 helper T cell-biased cellular immune response in rodents. Moreover, the vaccine candidate elicited long-term immunity and protection against SFTSV for at least 5 months. Notably, it provided complete cross-protection against other bandaviruses, such as the Heartland virus and Guertu virus, in lethal challenge models. Further research revealed that the conserved epitopes among bandaviruses within the full-length SFTSV glycoprotein may facilitate broad-spectrum protection mediated by the cellular immune response. Collectively, these findings demonstrate that the full-length SFTSV glycoprotein mRNA vaccine is a promising vaccine candidate for SFTSV and other bandaviruses, and provide guidance for the development of broad-spectrum vaccines from conserved antigens and epitopes. IMPORTANCE: Tick-borne bandaviruses, such as SFTSV and Heartland virus, sporadically trigger outbreaks in addition to influenza viruses and coronaviruses, yet there are no specific vaccines or therapeutics against them. mRNA vaccine technology has advantages in terms of enabling in situ expression and triggering cellular immunity, thus offering new solutions for vaccine development against intractable viruses, such as bandaviruses. In this study, we developed a novel vaccine candidate for SFTSV by employing mRNA vaccination technology and using a full-length glycoprotein as an antigen target. This candidate vaccine confers complete and durable protection against SFTSV at a notably low dose while also providing cross-protection against Heartland virus and Guertu virus. This study highlights the prospective value of full-length SFTSV-glycoprotein-based mRNA vaccines and suggests a potential strategy for broad-spectrum bandavirus vaccines.

Impact of stress hyperglycemia ratio on mortality in patients with cardiac arrest: insight from American MIMIC-IV database.

Background: Stress hyperglycemia ratio (SHR) has shown a predominant correlation with transient adverse events in critically ill patients. However, there remains a gap in comprehensive research regarding the association between SHR and mortality among patients experiencing cardiac arrest and admitted to the intensive care unit (ICU). Methods: A total of 535 patients with their initial ICU admission suffered cardiac arrest, according to the American Medical Information Mart for Intensive Care (MIMIC)-IV database. Patients were stratified into four categories based on quantiles of SHR. Multivariable Cox regression models were used to evaluate the association SHR and mortality. The association between SHR and mortality was assessed using multivariable Cox regression models. Subgroup analyses were conducted to determine whether SHR influenced ICU, 1-year, and long-term all-cause mortality in subgroups stratified according to diabetes status. Results: Patients with higher SHR, when compared to the reference quartile 1 group, exhibited a greater risk of ICU mortality (adjusted hazard ratio [aHR] = 3.029; 95% CI: 1.802-5.090), 1-year mortality (aHR = 3.057; 95% CI: 1.885-4.958), and long-term mortality (aHR = 3.183; 95% CI: 2.020-5.015). This association was particularly noteworthy among patients without diabetes, as indicated by subgroup analysis. Conclusion: Elevated SHR was notably associated with heightened risks of ICU, 1-year, and long-term all-cause mortality among cardiac arrest patients. These findings underscore the importance of considering SHR as a potential prognostic factor in the critical care management of cardiac arrest patients, warranting further investigation and clinical attention.

Follicular CD8+ T cells promote immunoglobulin production and demyelination in multiple sclerosis and a murine model.

Emerging evidence underscores the importance of CD8+ T cells in the pathogenesis of multiple sclerosis (MS), but the precise mechanisms remain ambiguous. This study intends to elucidate the involvement of a novel subset of follicular CD8+ T cells (CD8+CXCR5+ T) in MS and an experimental autoimmune encephalomyelitis (EAE) murine model. The expansion of CD8+CXCR5+ T cells was observed in both MS patients and EAE mice during the acute phase. In relapsing MS patients, higher frequencies of circulating CD8+CXCR5+ T cells were positively correlated with new gadolinium-enhancement lesions in the central nervous system (CNS). In EAE mice, frequencies of CD8+CXCR5+ T cells were also positively correlated with clinical scores. These cells were found to infiltrate into ectopic lymphoid-like structures in the spinal cords during the peak of the disease. Furthermore, CD8+CXCR5+ T cells, exhibiting high expression levels of ICOS, CD40L, IL-21, and IL-6, were shown to facilitate B cell activation and differentiation through a synergistic interaction between CD40L and IL-21. Transferring CD8+CXCR5+ T cells into naïve mice confirmed their ability to enhance the production of anti-MOG35-55 antibodies and contribute to the disease progression. Consequently, CD8+CXCR5+ T cells may play a role in CNS demyelination through heightening humoral immune responses.

A 'rich-get-richer' mechanism drives patchy dynamics and resistance evolution in antibiotic-treated bacteria.

Bacteria in nature often form surface-attached communities that initially comprise distinct subpopulations, or patches. For pathogens, these patches can form at infection sites, persist during antibiotic treatment, and develop into mature biofilms. Evidence suggests that patches can emerge due to heterogeneity in the growth environment and bacterial seeding, as well as cell-cell signaling. However, it is unclear how these factors contribute to patch formation and how patch formation might affect bacterial survival and evolution. Here, we demonstrate that a 'rich-get-richer' mechanism drives patch formation in bacteria exhibiting collective survival (CS) during antibiotic treatment. Modeling predicts that the seeding heterogeneity of these bacteria is amplified by local CS and global resource competition, leading to patch formation. Increasing the dose of a non-eradicating antibiotic treatment increases the degree of patchiness. Experimentally, we first demonstrated the mechanism using engineered Escherichia coli and then demonstrated its applicability to a pathogen, Pseudomonas aeruginosa. We further showed that the formation of P. aeruginosa patches promoted the evolution of antibiotic resistance. Our work provides new insights into population dynamics and resistance evolution during surface-attached bacterial growth.

Data-driven learning of structure augments quantitative prediction of biological responses.

Multi-factor screenings are commonly used in diverse applications in medicine and bioengineering, including optimizing combination drug treatments and microbiome engineering. Despite the advances in high-throughput technologies, large-scale experiments typically remain prohibitively expensive. Here we introduce a machine learning platform, structure-augmented regression (SAR), that exploits the intrinsic structure of each biological system to learn a high-accuracy model with minimal data requirement. Under different environmental perturbations, each biological system exhibits a unique, structured phenotypic response. This structure can be learned based on limited data and once learned, can constrain subsequent quantitative predictions. We demonstrate that SAR requires significantly fewer data comparing to other existing machine-learning methods to achieve a high prediction accuracy, first on simulated data, then on experimental data of various systems and input dimensions. We then show how a learned structure can guide effective design of new experiments. Our approach has implications for predictive control of biological systems and an integration of machine learning prediction and experimental design.

Automated cooling tower detection through deep learning for Legionnaires' disease outbreak investigations: a model development and validation study.

BACKGROUND: Cooling towers containing Legionella spp are a high-risk source of Legionnaires' disease outbreaks. Manually locating cooling towers from aerial imagery during outbreak investigations requires expertise, is labour intensive, and can be prone to errors. We aimed to train a deep learning computer vision model to automatically detect cooling towers that are aerially visible. METHODS: Between Jan 1 and 31, 2021, we extracted satellite view images of Philadelphia (PN, USA) and New York state (NY, USA) from Google Maps and annotated cooling towers to create training datasets. We augmented training data with synthetic data and model-assisted labelling of additional cities. Using 2051 images containing 7292 cooling towers, we trained a two-stage model using YOLOv5, a model that detects objects in images, and EfficientNet-b5, a model that classifies images. We assessed the primary outcomes of sensitivity and positive predictive value (PPV) of the model against manual labelling on test datasets of 548 images, including from two cities not seen in training (Boston [MA, USA] and Athens [GA, USA]). We compared the search speed of the model with that of manual searching by four epidemiologists. FINDINGS: The model identified visible cooling towers with 95·1% sensitivity (95% CI 94·0-96·1) and a PPV of 90·1% (95% CI 90·0-90·2) in New York City and Philadelphia. In Boston, sensitivity was 91·6% (89·2-93·7) and PPV was 80·8% (80·5-81·2). In Athens, sensitivity was 86·9% (75·8-94·2) and PPV was 85·5% (84·2-86·7). For an area of New York City encompassing 45 blocks (0·26 square miles), the model searched more than 600 times faster (7·6 s; 351 potential cooling towers identified) than did human investigators (mean 83·75 min [SD 29·5]; mean 310·8 cooling towers [42·2]). INTERPRETATION: The model could be used to accelerate investigation and source control during outbreaks of Legionnaires' disease through the identification of cooling towers from aerial imagery, potentially preventing additional disease spread. The model has already been used by public health teams for outbreak investigations and to initialise cooling tower registries, which are considered best practice for preventing and responding to outbreaks of Legionnaires' disease. FUNDING: None.

A single-cell transcriptome atlas of human euploid and aneuploid blastocysts.

Aneuploidy is frequently detected in early human embryos as a major cause of early pregnancy failure. However, how aneuploidy affects cellular function remains elusive. Here, we profiled the transcriptomes of 14,908 single cells from 203 human euploid and aneuploid blastocysts involving autosomal and sex chromosomes. Nearly all of the blastocysts contained four lineages. In aneuploid chromosomes, 19.5% ± 1.2% of the expressed genes showed a dosage effect, and 90 dosage-sensitive domains were identified. Aneuploidy leads to prevalent genome-wide transcriptome alterations. Common effects, including apoptosis, were identified, especially in monosomies, partially explaining the lower cell numbers in autosomal monosomies. We further identified lineage-specific effects causing unstable epiblast development in aneuploidies, which was accompanied by the downregulation of TGF-ß and FGF signaling, which resulted in insufficient trophectoderm maturation. Our work provides crucial insights into the molecular basis of human aneuploid blastocysts and may shed light on the cellular interaction during blastocyst development.

Temporal regulation of MDA5 inactivation by Caspase-3 dependent cleavage of 14-3-3η.

The kinetics of type I interferon (IFN) induction versus the virus replication compete, and the result of the competition determines the outcome of the infection. Chaperone proteins that involved in promoting the activation kinetics of PRRs rapidly trigger antiviral innate immunity. We have previously shown that prior to the interaction with MAVS to induce type I IFN, 14-3-3η facilitates the oligomerization and intracellular redistribution of activated MDA5. Here we report that the cleavage of 14-3-3η upon MDA5 activation, and we identified Caspase-3 activated by MDA5-dependent signaling was essential to produce sub-14-3-3η lacking the C-terminal helix (αI) and tail. The cleaved form of 14-3-3η (sub-14-3-3η) could strongly interact with MDA5 but could not support MDA5-dependent type I IFN induction, indicating the opposite functions between the full-length 14-3-3η and sub-14-3-3η. During human coronavirus or enterovirus infections, the accumulation of sub-14-3-3η was observed along with the activation of Caspase-3, suggesting that RNA viruses may antagonize 14-3-3η by promoting the formation of sub-14-3-3η to impair antiviral innate immunity. In conclusion, sub-14-3-3η, which could not promote MDA5 activation, may serve as a negative feedback to return to homeostasis to prevent excessive type I IFN production and unnecessary inflammation.

Machine learning in soil nutrient dynamics of alpine grasslands.

As a terrestrial ecosystem, alpine grasslands feature diverse vegetation types and play key roles in regulating water resources and carbon storage, thus shaping global climate. The dynamics of soil nutrients in this ecosystem, responding to regional climate change, directly impact primary productivity. This review comprehensively explored the effects of climate change on soil nitrogen (N), phosphorus (P), and their balance in the alpine meadows, highlighting the significant roles these nutrients played in plant growth and species diversity. We also shed light on machine learning utilization in soil nutrient evaluation. As global warming continues, alongside shifting precipitation patterns, soil characteristics of grasslands, such as moisture and pH values vary significantly, further altering the availability and composition of soil nutrients. The rising air temperature in alpine regions substantially enhances the activity of soil organisms, accelerating nutrient mineralization and the decomposition of organic materials. Combined with varied nutrient input, such as increased N deposition, plant growth and species composition are changing. With the robust capacity to use and integrate diverse data sources, including satellite imagery, sensor-collected spectral data, camera-captured videos, and common knowledge-based text and audio, machine learning offers rapid and accurate assessments of the changes in soil nutrients and associated determinants, such as soil moisture. When combined with powerful large language models like ChatGPT, these tools provide invaluable insights and strategies for effective grassland management, aiming to foster a sustainable ecosystem that balances high productivity and advanced services with reduced environmental impacts.

Automatic classification of fetal heart rate based on a multi-scale LSTM network.

Introduction: Fetal heart rate monitoring during labor can aid healthcare professionals in identifying alterations in the heart rate pattern. However, discrepancies in guidelines and obstetrician expertise present challenges in interpreting fetal heart rate, including failure to acknowledge findings or misinterpretation. Artificial intelligence has the potential to support obstetricians in diagnosing abnormal fetal heart rates. Methods: Employ preprocessing techniques to mitigate the effects of missing signals and artifacts on the model, utilize data augmentation methods to address data imbalance. Introduce a multi-scale long short-term memory neural network trained with a variety of time-scale data for automatically classifying fetal heart rate. Carried out experimental on both single and multi-scale models. Results: The results indicate that multi-scale LSTM models outperform regular LSTM models in various performance metrics. Specifically, in the single models tested, the model with a sampling rate of 10 exhibited the highest classification accuracy. The model achieves an accuracy of 85.73%, a specificity of 85.32%, and a precision of 85.53% on CTU-UHB dataset. Furthermore, the area under the receiver operating curve of 0.918 suggests that our model demonstrates a high level of credibility. Discussion: Compared to previous research, our methodology exhibits superior performance across various evaluation metrics. By incorporating alternative sampling rates into the model, we observed improvements in all performance indicators, including ACC (85.73% vs. 83.28%), SP (85.32% vs. 82.47%), PR (85.53% vs. 82.84%), recall (86.13% vs. 84.09%), F1-score (85.79% vs. 83.42%), and AUC(0.9180 vs. 0.8667). The limitations of this research include the limited consideration of pregnant women's clinical characteristics and disregard the potential impact of varying gestational weeks.

A near-infrared fluorescent probe for the detection of Cu2+ in Chinese herbal medicine and imaging in living cells.

Copper is one of the common among the heavy metal pollution in Chinese herbal medicine (CHM). So, it is essential to develop rapid and accurate testing method to quantify the Cu2+ content in CHM. Herein, we prepared a coordination-based near-infrared fluorescent probe (NRh6G-FA) by introducing a hemicyanine dye in rhodamine 6G scaffold. NRh6G-FA had a high sensitivity, anti-interference performance, fast response (within 60 s), visualization (from light yellow to green) for Cu2+ and excellent sensing performance for the detection of Cu2+ at low concentrations (LOD = 0.225 µM). The most likely mechanism was verified on the basis of Job's plot, ESI-HRMS and DFT calculations. NRh6G-FA could be successfully applied for the detection and "naked eye" recognition of Cu2+ in CHM samples. Moreover, NRh6G-FA was used to visualize Cu2+ in living MCF-7 cells by confocal fluorescence imaging.

Curcumin affects autophagy of prolactinoma cells by upregulating miR-206 to exert antitumor effects.

We explored the effects of curcumin on the aberrant biological behaviors of prolactinoma cells and the downstream pathways through which curcumin exerts its antitumor effects. We used quantitative reverse transcription-polymerase chain reaction assays to measure miR-206 expression levels in peripheral blood samples from patients with prolactinoma before and after curcumin treatment. We also investigated the proliferation level, viability, and invasion ability of groups of cells treated with different concentrations of curcumin using 3-(4,5)-dimethylthiahiazo (-z-y1)-3-di-phenytetrazoliumromide (MTT) assays, cell cloning assays, and Transwell assays, respectively. Furthermore, we determined the levels of autophagy-related proteins and protein kinase B/mammalian target of the rapamycin (Akt/mTOR) signaling pathway-related proteins in each group of treated cells by western blot. Curcumin treatment upregulated miR-206 expression levels in the peripheral blood of patients with prolactinoma and in GH3 cells. Knockdown of miR-206 expression enhanced the proliferation and invasive ability of GH3 cells, while curcumin treatment effectively inhibited the aberrant biological behavior of GH3 cells enhanced by miR-206 knockdown. miR-206 knockdown also activated the Akt/mTOR signaling pathway and inhibited autophagy in GH3 cells, and these changes were effectively reversed by curcumin treatment. Thus, curcumin inhibited the Akt/mTOR signaling pathway and promoted cell autophagy by miR-206 upregulation, resulting in antitumor effects that inhibited prolactinoma cell proliferation and invasion.

Self-healing propagation of a longitudinally varying vector optical beam for distance measurement.

Based on the longitudinal manipulation of polarization, a special vector optical beam (VOB) with customized polarization variation in propagation direction can be generated, whose properties and applications remain to be studied. Here, the self-healing propagation behaviors of the longitudinally varying VOB after an opaque object are investigated, and the localized polarization responses on the object distance are revealed. On this basis, characteristic parameters are defined to measure the distance of object, achieving a minimum relative error of 0.63% in a longitudinal range of 300 mm. Besides, the correlations and uncoupling methods of object distance and size are discussed. Our studies open new ways to use the structural properties of VOB and may be instructive for laser measurement.

Heme metabolism and HO-1 in the pathogenesis and potential intervention of endometriosis.

Endometriosis (EM) is one of the diseases related to retrograded menstruation and hemoglobin. Heme, released from hemoglobin, is degraded by heme oxygenase-1 (HO-1). In EM lesions, heme metabolites regulate processes such as inflammation, redox balance, autophagy, dysmenorrhea, malignancy, and invasion, where macrophages (Mø) play a fundamental role in their interactions. Regulation occurs at molecular, cellular, and pathological levels. Numerous studies suggest that heme is an indispensable component in EM and may contribute to its pathogenesis. The regulatory role of heme in EM encompasses cytokines, signaling pathways, and kinases that mediate cellular responses to external stimuli. HO-1, a catalytic enzyme in the catabolic phase of heme, mitigates heme's cytotoxicity in EM due to its antioxidant, anti-inflammatory, and anti-proliferative properties. Certain compounds may intervene in EM by targeting heme metabolism, guiding the development of appropriate treatments for all stages of endometriosis.

Age-dependent distribution of IgA and IgG antibody-secreting cells in the pharyngeal tonsil of the Bactrian camel.

The pharyngeal tonsil, located in the nasopharynx, can effectively defend against pathogens invading the body from the upper respiratory tract and play a crucial role in mucosal immunity of the respiratory tract. Immunoglobulin A (IgA) and Immunoglobulin G (IgG) serve as key effector molecules in mucosal immunity, exhibiting multiple immune functions. This study aimed to investigate the distribution patterns and age-related alterations of IgA and IgG antibody-secreting cells (ASCs) in the pharyngeal tonsils of Bactrian camels. Twelve Alashan Bactrian camels were categorized into four age groups: young (1-2 years, n=3), pubertal (3-5 years, n=3), middle-aged (6-16 years, n=3) and old (17-20 years, n=3). The distribution patterns of IgA and IgG ASCs in the pharyngeal tonsils of Bactrian camels of different ages were meticulously observed, analyzed and compared using immunohistochemical and statistical methods. The results revealed that IgA ASCs in the pharyngeal tonsils of all age groups were primarily clustered or diffusely distributed in the reticular epithelium and its subepithelial regions (region A) and around the glands (region C), scattered in the subepithelial regions of non-reticular epithelium (region B), and sporadically distributed in the interfollicular regions (region D). Interestingly, the distribution pattern of IgG ASCs in the pharyngeal tonsils closely mirrored that of IgA ASCs. The distribution densities of IgA and IgG ASCs in these four regions were significantly decreased in turn (P<0.05). However, IgA ASCs exhibited significantly higher densities than IgG ASCs in the same region (P<0.05). Age-related alterations indicated that the distribution densities of IgA and IgG ASCs in each region of the pharyngeal tonsils exhibited a trend of initially increasing and subsequently decreasing from young to old camels, reaching a peak in the pubertal group. As camels age, there was a significant decrease in the densities of IgA and IgG ASCs in all regions of the pharyngeal tonsils (P<0.05). The results demonstrate that the reticular epithelium and its subepithelial regions in the pharyngeal tonsils of Bactrian camels are the primary regions where IgA and IgG ASCs colonize and exert their immune functions. These regions play a pivotal role in inducing immune responses and defending against pathogen invasions in the pharyngeal tonsils. IgA ASCs may be the principal effector cells of the mucosal immune response in the pharyngeal tonsils of Bactrian camels. Aging significantly reduces the densities of IgA and IgG ASCs, while leaving their distribution patterns unaffected. These findings will provide valuable insights for further investigations into the immunomorphology, immunosenescence, and response mechanisms of the pharyngeal tonsils in Bactrian camels.

Altered regional brain activity and functional connectivity in primary intravaginal anejaculation patients revealed by resting-state fMRI.

ABSTRACT: Ejaculation is regulated by the central nervous system. However, the central pathophysiology of primary intravaginal anejaculation (PIAJ) is unclear. The present study aimed to examine the changes in regional brain activity and functional connectivity underlying PIAJ. A total of 20 PIAJ patients and 16 healthy controls (HCs) were enrolled from September 2020 to September 2022 in the Department of Andrology, Nanjing Drum Tower Hospital (Nanjing, China). Magnetic resonance imaging data were acquired from all participants and then were preprocessed. The measures of fractional amplitude of low-frequency fluctuation (fALFF), regional homogeneity (ReHo), and functional connectivity (FC) were calculated and compared between the groups. PIAJ patients showed increased fALFF values in the left precuneus compared with HCs. Additionally, PIAJ patients showed increased ReHo values in the left precuneus, left postcentral gyrus, left superior occipital gyrus, left calcarine fissure, right precuneus, and right middle temporal gyrus, and decreased ReHo values in the left inferior parietal gyrus, compared with HCs. Finally, brain regions with altered fALFF and ReHo values in PIAJ patients showed increased FC with widespread cortical regions, which included the frontal, parietal, temporal, and occipital regions, compared with HCs. In conclusion, increased regional brain activity in the parietal, temporal, and occipital regions, and increased FC between these brain regions, may be associated with PIAJ occurrence.

Revealing the spatiotemporal brain dynamics of covert speech compared with overt speech: A simultaneous EEG-fMRI study.

Covert speech (CS) refers to speaking internally to oneself without producing any sound or movement. CS is involved in multiple cognitive functions and disorders. Reconstructing CS content by brain-computer interface (BCI) is also an emerging technique. However, it is still controversial whether CS is a truncated neural process of overt speech (OS) or involves independent patterns. Here, we performed a word-speaking experiment with simultaneous EEG-fMRI. It involved 32 participants, who generated words both overtly and covertly. By integrating spatial constraints from fMRI into EEG source localization, we precisely estimated the spatiotemporal dynamics of neural activity. During CS, EEG source activity was localized in three regions: the left precentral gyrus, the left supplementary motor area, and the left putamen. Although OS involved more brain regions with stronger activations, CS was characterized by an earlier event-locked activation in the left putamen (peak at 262 ms versus 1170 ms). The left putamen was also identified as the only hub node within the functional connectivity (FC) networks of both OS and CS, while showing weaker FC strength towards speech-related regions in the dominant hemisphere during CS. Path analysis revealed significant multivariate associations, indicating an indirect association between the earlier activation in the left putamen and CS, which was mediated by reduced FC towards speech-related regions. These findings revealed the specific spatiotemporal dynamics of CS, offering insights into CS mechanisms that are potentially relevant for future treatment of self-regulation deficits, speech disorders, and development of BCI speech applications.