Tag: pubmed

Anesthesiology. 2025 Apr 3. doi: 10.1097/ALN.0000000000005479. Online ahead of print.

ABSTRACT

BACKGROUND: The conscious state is maintained through intact communication between brain regions. However, studies on global and regional connectivity changes in unconscious state have been inconsistent. These inconsistencies could arise from unclear definition of unconsciousness, spatial and temporal limitations of neuroimaging modalities, and estimating only single connectivity measure. Here, we investigated global and regional changes in amplitude and phase based functional connectivity in propofol-induced unconsciousness, which is widely recognized as unconsciousness.

METHODS: We calculated amplitude and phase based functional connectivity using amplitude envelope correlation (AEC), weighted phase lag index (wPLI), and magnitude squared coherence (MSC) from intracranial electroencephalography data of 73 patients. Global changes in connectivity, complexity, and network efficiency were estimated. Regional connectivity changes between Brodmann areas, between 7 cortical lobes, and between resting state networks were assessed across all frequency bands. Additionally, we employed machine learning analysis to identify specific regions in classifying conscious and unconscious states.

RESULTS: In the unconscious state, global connectivity increased across all frequency bands, while global complexity and efficiency decreased, accompanied by increased delta and decreased high gamma power spectral density. Regional connectivity increased between entire cortical regions across all frequency bands. Machine learning analysis revealed that posterior connectivity was the most influential in classifying consciousness. Amplitude-based connectivity predominantly increased in the delta and theta bands, while phase-based connectivity predominantly increased from the beta to high gamma bands.

CONCLUSIONS: Propofol anesthesia suppresses cortical activity and induces oscillatory changes characterized by increased delta power and decreased high gamma power. These changes are accompanied by increased functional connectivity and reduced network complexity and efficiency. These changes limit the brain’s ability to generate a diverse repertoire of activity, ultimately leading to unconsciousness. Posterior connectivity, which showed high accuracy in predicting conscious states, would be crucial for sustaining consciousness.

PMID:40179374 | DOI:10.1097/ALN.0000000000005479

JMIR AI. 2025 Apr 3;4:e68809. doi: 10.2196/68809.

ABSTRACT

BACKGROUND: Most online and social media discussions about birth control methods for women center on side effects, highlighting a demand for shared experiences with these products. Online user reviews and ratings of birth control products offer a largely untapped supplementary resource that could assist women and their partners in making informed contraception choices.

OBJECTIVE: This study sought to analyze women’s online ratings and reviews of various birth control methods, focusing on side effects linked to low product ratings.

METHODS: Using natural language processing (NLP) for topic modeling and descriptive statistics, this study analyzes 19,506 unique reviews of female contraceptive products posted on the website Drugs.com.

RESULTS: Ratings vary widely across contraception types. Hormonal contraceptives with high systemic absorption, such as progestin-only pills and extended-cycle pills, received more unfavorable reviews than other methods and women frequently described menstrual irregularities, continuous bleeding, and weight gain associated with their administration. Intrauterine devices were generally rated more positively, although about 1 in 10 users reported severe cramps and pain, which were linked to very poor ratings.

CONCLUSIONS: While exploratory, this study highlights the potential of NLP in analyzing extensive online reviews to reveal insights into women’s experiences with contraceptives and the impact of side effects on their overall well-being. In addition to results from clinical studies, NLP-derived insights from online reviews can provide complementary information for women and health care providers, despite possible biases in online reviews. The findings suggest a need for further research to validate links between specific side effects, contraceptive methods, and women’s overall well-being.

PMID:40179373 | DOI:10.2196/68809

J Med Internet Res. 2025 Apr 3;27:e63090. doi: 10.2196/63090.

ABSTRACT

BACKGROUND: Floodlight Open is a global, open-access, fully remote, digital-only study designed to understand the drivers and barriers in deployment and persistence of use of a smartphone app for measuring functional impairment in a naturalistic setting and broad study population.

OBJECTIVE: This study aims to assess measurement equivalence properties of the Floodlight Open app across operating system (OS) platforms, OS versions, and smartphone device models.

METHODS: Floodlight Open enrolled adult participants with and without self-declared multiple sclerosis (MS). The study used the Floodlight Open app, a “bring-your-own-device” (BYOD) solution that remotely measured MS-related functional ability via smartphone sensor-based active tests. Measurement equivalence was assessed in all evaluable participants by comparing the performance on the 6 active tests (ie, tests requiring active input from the user) included in the app across OS platforms (iOS vs Android), OS versions (iOS versions 11-15 and separately Android versions 8-10; comparing each OS version with the other OS versions pooled together), and device models (comparing each device model with all remaining device models pooled together). The tests in scope were Information Processing Speed, Information Processing Speed Digit-Digit (measuring reaction speed), Pinching Test (PT), Static Balance Test, U-Turn Test, and 2-Minute Walk Test. Group differences were assessed by permutation test for the mean difference after adjusting for age, sex, and self-declared MS disease status.

RESULTS: Overall, 1976 participants using 206 different device models were included in the analysis. Differences in test performance between subgroups were very small or small, with percent differences generally being ≤5% on the Information Processing Speed, Information Processing Speed Digit-Digit, U-Turn Test, and 2-Minute Walk Test; <20% on the PT; and <30% on the Static Balance Test. No statistically significant differences were observed between OS platforms other than on the PT (P<.001). Similarly, differences across iOS or Android versions were nonsignificant after correcting for multiple comparisons using false discovery rate correction (all adjusted P>.05). Comparing the different device models revealed a statistically significant difference only on the PT for 4 out of 17 models (adjusted P≤.001-.03).

CONCLUSIONS: Consistent with the hypothesis that smartphone sensor-based measurements obtained with different devices are equivalent, this study showed no evidence of a systematic lack of measurement equivalence across OS platforms, OS versions, and device models on 6 active tests included in the Floodlight Open app. These results are compatible with the use of smartphone-based tests in a bring-your-own-device setting, but more formal tests of equivalence would be needed.

PMID:40179369 | DOI:10.2196/63090

Nutr Health. 2025 Apr 3:2601060251327714. doi: 10.1177/02601060251327714. Online ahead of print.

ABSTRACT

Background: The World Health Organization forecasts that depression will become the world’s second most common illness by 2030 and affect people of all ages. Meanwhile, in Indonesia, approximately 1 in 100 people experience depression, with the highest prevalence found in the age group of 15-24 years, at 2%. Adjusting one’s diet, as suggested by the Antidepressant Food Score (AFS) list, presents a promising method for managing and addressing depression. Aim: To find out the association between the AFS and depression levels. Methods: This cross-sectional study in Surabaya, Indonesia, included 374 participants aged 15-17 years. Antidepressant food intake was assessed using the Semi-Quantitative Food Frequency Questionnaire, while depression levels were measured with the Center for Epidemiologic Studies Depression Scale. Additionally, social and psychological factors were considered. The data were analyzed using STATA. Results: A significant difference in daily fruit and vegetable consumption was found between adolescents with mild and moderate depression. Those with mild depression had an average AFS of 86.03%, while those with moderate depression had 66.28%. Although the AFS was associated with depression (p = 0.031), it did not have a statistically significant impact on depression levels after adjusting for factors such as age, sex, social support, stress and problem-solving ability (odds ratio = 1.54, 95% confidence interval = 0.94, 2.50). Conclusion: This study identified a statistically significant association between AFS and depression levels. However, after adjusting for other predictors, this association did not remain statistically significant. Future research should focus on developing a more comprehensive database of antidepressant food lists in Indonesia.

PMID:40179358 | DOI:10.1177/02601060251327714

J Cardiovasc Nurs. 2025 Apr 3. doi: 10.1097/JCN.0000000000001203. Online ahead of print.

ABSTRACT

BACKGROUND: Research on the care needs of patients with heart failure (HF) has predominantly relied on cross-sectional studies. Consequently, there is limited understanding of how care needs evolve over time within this population.

OBJECTIVES: The aims of this study were to explore the trajectories of care needs in patients with HF 1 year after discharge and analyze the potential factors that can predict these trajectories.

METHODS: A total of 197 patients with HF were recruited and followed at 1, 3, 6, and 12 months postdischarge. Care needs were assessed using the care needs survey questionnaire, and potential factors were selected based on the Andersen Behavioral Model. A growth mixture model was used to identify the trajectories of care needs, whereas logistic regression analyses were used for statistical comparisons.

RESULTS: Three trajectories in the care needs of patients with HF were identified: (1) a mild increase trajectory, (2) a decline trajectory, and (3) a persistently high trajectory. Need factors were the most significant determinants of care needs trajectories, with higher New York Heart Association functional classification, left ventricular ejection fraction less than 40%, and lower self-reported health serving as key predictors of persistently high trajectory. In contrast, only lower self-efficacy and the absence of a spouse as predisposing factors were associated with an increased risk of maintaining persistently high levels of care needs.

CONCLUSION: Care needs after discharge in patients with HF can be characterized by 3 trajectories. Need factors will help clinicians with early identification of patients with persistently high level of care needs.

PMID:40179353 | DOI:10.1097/JCN.0000000000001203

PLoS Comput Biol. 2025 Apr 3;21(4):e1012878. doi: 10.1371/journal.pcbi.1012878. eCollection 2025.

ABSTRACT

The advent of 5′ single-cell RNA sequencing (scRNA-seq) technologies offers unique opportunities to identify and analyze transcription start sites (TSSs) at a single-cell resolution. These technologies have the potential to uncover the complexities of transcription initiation and alternative TSS usage across different cell types and conditions. Despite the emergence of computational methods designed to analyze 5′ RNA sequencing data, current methods often lack comparative evaluations in single-cell contexts and are predominantly tailored for paired-end data, neglecting the potential of single-end data. This study introduces scTSS, a computational pipeline developed to bridge this gap by accommodating both paired-end and single-end 5′ scRNA-seq data. scTSS enables joint analysis of multiple single-cell samples, starting with TSS cluster prediction and quantification, followed by differential TSS usage analysis. It employs a Binomial generalized linear mixed model to accurately and efficiently detect differential TSS usage. We demonstrate the utility of scTSS through its application in analyzing transcriptional initiation from single-cell data of two distinct diseases. The results illustrate scTSS’s ability to discern alternative TSS usage between different cell types or biological conditions and to identify cell subpopulations characterized by unique TSS-level expression profiles.

PMID:40179341 | DOI:10.1371/journal.pcbi.1012878

PLoS Comput Biol. 2025 Apr 3;21(4):e1012881. doi: 10.1371/journal.pcbi.1012881. eCollection 2025 Apr.

ABSTRACT

Understanding the spatial locations of cell within tissues is crucial for unraveling the organization of cellular diversity. Recent advancements in spatial resolved transcriptomics (SRT) have enabled the analysis of gene expression while preserving the spatial context within tissues. Spatial domain characterization is a critical first step in SRT data analysis, providing the foundation for subsequent analyses and insights into biological implications. Graph neural networks (GNNs) have emerged as a common tool for addressing this challenge due to the structural nature of SRT data. However, current graph-based deep learning approaches often overlook the instability caused by the high sparsity of SRT data. Masking mechanisms, as an effective self-supervised learning strategy, can enhance the robustness of these models. To this end, we propose SpaMask, dual masking graph autoencoder with contrastive learning for SRT analysis. Unlike previous GNNs, SpaMask masks a portion of spot nodes and spot-to-spot edges to enhance its performance and robustness. SpaMask combines Masked Graph Autoencoders (MGAE) and Masked Graph Contrastive Learning (MGCL) modules, with MGAE using node masking to leverage spatial neighbors for improved clustering accuracy, while MGCL applies edge masking to create a contrastive loss framework that tightens embeddings of adjacent nodes based on spatial proximity and feature similarity. We conducted a comprehensive evaluation of SpaMask on eight datasets from five different platforms. Compared to existing methods, SpaMask achieves superior clustering accuracy and effective batch correction.

PMID:40179332 | DOI:10.1371/journal.pcbi.1012881

J Clin Oncol. 2025 Apr 3:JCO2401818. doi: 10.1200/JCO-24-01818. Online ahead of print.

ABSTRACT

PURPOSE: Although multiple agents targeting PD-1 have been approved as second-line treatment for esophageal squamous cell carcinoma (ESCC), only a fraction of patients derive long-term survival. Hence, reliable predictive biomarkers are urgently needed.

METHODS: Comprehensive tumor genomic profiling and transcriptome sequencing were performed on samples from the RATIONALE-302 study. We also conducted single-cell RNA sequencing analysis on Notch1 knockdown ESCC murine models to further explore the potential molecular mechanisms underlying anti-PD-1 benefit.

RESULTS: We identified NOTCH1 mutation as a potential predictive biomarker for longer overall survival (OS) with tislelizumab versus chemotherapy (18.4 months v 5.3 months; hazard ratio, 0.35 [95% CI, 0.17 to 0.71]). At the transcriptional level, type I IFN (IFN-I)/toll-like receptor expression signatures were positively associated with OS benefit of tislelizumab, whereas B-cell and neutrophil signatures predicted unfavorable OS. Exploratory analyses showed that the presence of NOTCH1 mutation correlated with enrichment of IFN-I signatures and reduced infiltration of B cells and neutrophils. In murine models, comparative single-cell transcriptome analyses further revealed that Notch1 deficiency facilitated a more immunologically activated tumor microenvironment which potentiated anti-PD-1 treatment.

CONCLUSION: Our data provide novel insights for anti-PD-1 treatment selection using NOTCH1 mutations and may provide a rationale for combination therapy in ESCC.

PMID:40179324 | DOI:10.1200/JCO-24-01818

PLoS One. 2025 Apr 3;20(4):e0320365. doi: 10.1371/journal.pone.0320365. eCollection 2025.

ABSTRACT

BACKGROUND: Heart failure (HF) is a growing health problem and around two percent are affected in the general population. Accurate diagnostic markers that have the potential for early diagnosis of HF are lacking. This study aimed to compare the expression levels of microRNA-210-3p with biomarkers NT-proBNP, sST2, and galectin-3, in heart failure patients with preserved and reduced ejection fractions.

MATERIALS AND METHODS: The cross-sectional study was conducted on 270 hypertensive heart failure patients in the age group of 30 to 75 years of both genders. The participants with evidence of HF were recruited from the Department of Cardiology in a tertiary care hospital in Chennai, India. MicroRNA-210-3p was analyzed by qRT-PCR in a stratified sample of 80 HF patients and 20 apparently healthy individuals. Biomarkers were analyzed by ELISA. Institutional ethics committee approval and written informed consent were obtained. Statistical analysis was performed using R software (4.2.1). Based on the type of distribution of data, appropriate statistical tools were used. p-value ≤ 0.05 was considered to be statistically significant.

RESULTS: All the biomarkers including microRNA-210-3p were significantly higher in HFrEF than in HFpEF. MAGGIC score showed a positive correlation with all the biomarkers. The cut-off of microRNA-210-3p was 5.03.

CONCLUSION: All the biomarkers were significantly elevated in HFrEF compared to HFpEF. However, microRNA-210-3p could be an early marker in the diagnosis of heart failure. The strategy of employing a multi-marker approach could help in the early diagnosis as well as in stratifying the HF patients.

PMID:40179320 | DOI:10.1371/journal.pone.0320365

Neurogastroenterol Motil. 2025 Apr 3:e70037. doi: 10.1111/nmo.70037. Online ahead of print.

ABSTRACT

BACKGROUND: Gut-directed hypnotherapy has been shown to be an effective treatment for irritable bowel syndrome, but prior studies have been small with variable delivery modalities. This systematic review and meta-analysis investigates the efficacy of gut-directed hypnotherapy for irritable bowel syndrome (IBS) symptoms and the impact of delivery characteristics.

METHODS: PubMed, Embase, and Web of Science were searched. Titles and abstracts, then full text articles, were screened for inclusion criteria. Studies were extracted and assessed for bias using the Cochrane Collaboration risk-of-bias tool. A meta-analysis was performed to assess the impact of gut-directed hypnotherapy on global IBS symptoms and pain. A sub-group analysis was conducted to assess the impact of gut-directed hypnotherapy delivery characteristics on IBS-related outcomes.

RESULTS: Twelve studies in 11 papers met inclusion criteria, involving 1158 patients with IBS. Eight studies provided continuous measures sufficient for meta-analysis. On systematic review, all 12 studies found gut-directed hypnotherapy to be superior to the comparator; nine were statistically significant. On meta-analysis, gut-directed hypnotherapy improved global IBS symptoms (SMD 0.73 [-0.09-1.55], I² 93%). Gut-directed hypnotherapy with high-volume delivery and gut-directed hypnotherapy delivered in groups showed statistically significant improvement in global IBS symptoms (SMD 0.56 [0.29-0.83], I² 0%; SMD 0.41 [0.05-0.77], I² 61%). Gut-directed hypnotherapy also significantly improved pain more than its comparator groups (SMD 0.25 [0.01-0.49], I² 17%).

CONCLUSION: Gut-directed hypnotherapy may improve global symptoms of IBS. In particular, GDH improved pain symptoms compared to other standard IBS interventions. GDH delivered in groups was effective at reducing global IBS symptoms compared to standard interventions.

PMID:40179285 | DOI:10.1111/nmo.70037