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Polyhedral Crystal Films of Covalent Organic Frameworks

Novel imaging diagnosis of neuropsychiatric systemic lupus erythematosus using topological data analysis: A retrospective study

Introduction Diagnosing neuropsychiatric systemic lupus erythematosus (NPSLE) and differentiating it from systemic lupus erythematosus (SLE) without neuropsychiatric manifestations remains a substantial clinical challenge due to the absence of specific biomarkers. Topological data analysis (TDA) is a novel computational technique that enables the visualization, exploration, and analysis of complex data structures. This study aimed to identify distinct neuroimaging biomarkers in patients with NPSLE (NPSLE group) and differentiate them from patients with SLE without neuropsychiatric symptoms (non-NPSLE group) by employing TDA. Methods We conducted a retrospective cohort study involving 30 patients with NPSLE and 30 without neuropsychiatric symptoms between 2005 and 2020. TDA was utilized to extract topological features, specifically connected components and holes, from fluid-attenuated inversion recovery (FLAIR) sequences obtained via brain magnetic resonance imaging (MRI). Summary statistics, including critical point count, persistence lifetime, centroid coordinates, perimeter, area, and filamentarity, were derived from persistence diagrams. Results Multiple logistic regression analyses, adjusted for age, cerebrovascular comorbidities, and 50% hemolytic unit of complement levels, demonstrated a significant association between NPSLE and the perimeter of the holes (odds ratio [OR]: 1.67, 95% confidence interval [CI]: 1.07–2.63, p = 0.025) and the area of the holes (OR: 4.42, 95% CI: 1.35–19.6, p = 0.026) of the identified topological features. Additionally, both areas under the receiver operating characteristic curve (AUC) exceeded 0.8, indicating good diagnostic accuracy. Conclusion This study identified novel neuroimaging biomarkers for the diagnosis of NPSLE. The application of TDA to brain MRI features in patients with SLE proved to be a valuable diagnostic tool, particularly through the analysis of persistence diagrams.

Formation of Lactic Acid (CH₃CH(OH)COOH), a Metabolic Keystone for the Molecular Origins of Life, in Interstellar Ice Analogues

The roles of binge gaming in social, academic and mental health outcomes and gender differences: A school-based survey in Hong Kong

Binge gaming, defined as playing video games for more than five consecutive hours, has become an emerging health and behavioral issue among children and adolescents. However, the potential factors and consequences have not been sufficiently investigated. This study aims to examine the prevalence of binge gaming, its social, academic, and mental health consequences, and potential gender differences among children and adolescents in Hong Kong. A school-based survey was conducted on 2,592 primary and secondary students in Hong Kong. The sample included 1,404 boys (mean age = 11.99 + /- 2.415 years) and 1,188 girls (mean age = 11.77 + /- 2.473 years), with an overall mean age of 11.89 years. Internet gaming disorder (IGD), depression, anxiety, stress, loneliness, social support, sleep quality, and educational self-efficacy were measured using well-validated self-report scales. Analysis of Covariance (ANCOVA) models, adjusting for age and daily gaming time, were employed to examine mental, social, and academic outcomes among binge gamers, non-binge gamers, and non-gamers. Subgroup analyses were conducted by gender. The overall prevalence of binge gaming in the study sample was 31.7%. Thirty percent of respondents reported at least one episode of binge gaming in the last month, with 38.3% in boys and 24.0% in girls. In boys, binge gamers showed greater IGD, depression, anxiety, and stress, poorer sleep quality, and lower educational self-efficacy than non-binge gamers. Similarly, female binge gamers exhibited higher IGD, depression, anxiety, stress, and loneliness, and lower educational self-efficacy, sleep quality, and social support. Non-gamers generally experienced less depression, anxiety, stress, and loneliness, and higher educational self-efficacy, than binge gamers in both genders. Binge gaming may act as a behavioral indicator and risk factor for various social, academic, and health problems and preventive effort is warranted.

Anti-obesity compounds, Semaglutide and LiPR, and PrRP do not change the proportion of human and mouse POMC+ neurons

Anti-obesity medications (AOMs) have become one of the most prescribed drugs in human medicine. While AOMs are known to impact adult neurogenesis in the hypothalamus, their effects on the functional maturation of hypothalamic neurons remain unexplored. Given that AOMs target neurons in the Medial Basal Hypothalamus (MBH), which play a crucial role in regulating energy homeostasis, we hypothesized that AOMs might influence the functional maturation of these neurons, potentially rewiring the MBH. To investigate this, we exposed hypothalamic neurons derived from human induced pluripotent stem cells (hiPSCs) to Semaglutide and lipidized prolactin-releasing peptide (LiPR), two anti-obesity compounds. Contrary to our expectations, treatment with Semaglutide or LiPR during neuronal maturation did not affect the proportion of anorexigenic, Pro-opiomelanocortin-expressing (POMC+) neurons. Additionally, LiPR did not alter the morphology of POMC+ neurons or the expression of selected genes critical for the metabolism or development of anorexigenic neurons. Furthermore, LiPR did not impact the proportion of adult-generated POMC+ neurons in the mouse MBH. Taken together, these results suggest that AOMs do not influence the functional maturation of anorexigenic hypothalamic neurons.

Catalytic Photooxygenation Demonstrates Therapeutic Efficacy in Transthyretin Amyloidosis

Evaluating the feasibility and preliminary impact of the Social, Emotional, and Ethical (SEE) Learning program: A compassion-based social and emotional learning program for elementary school children

Objectives This study aimed to assess the feasibility and preliminary outcomes of the SEE Learning® (Social, Emotional, and Ethical Learning) program among elementary school-aged children. Methodology A quasi-experimental design was employed, with 685 4th- and 5th-grade students across 33 classrooms (344 students received the 12-week SEE Learning program; 341 students were wait-list controls). Assessments of compassion for self and others, social and emotional competencies, and the degree to which students perceived their classrooms as supportive were collected before and after program implementation. Measures of dosage, fidelity, and acceptability were assessed via teachers’ weekly lesson diaries. Results Teachers reported the program was feasible to implement. They demonstrated high lesson completion and fidelity rates with minimal preparation time and strong adherence to the lesson structure. Most program activities fit within a 50-minute timeframe or less, reflecting the program’s suitability for elementary school settings. Student reports showed preliminary impacts of the program. Those who received SEE Learning reported significant improvements in self-compassion, perspective-taking, empathic concern (e.g., compassion for others), intrinsic prosocial motivation, and academic goal setting compared to students in the wait-list control group. Significance This study is among the first to demonstrate the feasibility and preliminary student impacts of the compassion-focused SEE Learning program in an elementary school setting. Future investigations might explore the implementation and effects of the SEE Learning program using randomized-controlled experimental designs and longer-term follow-ups. In addition, studies evaluating program implementation and impacts in diverse cultural-contextual settings, and among students of different ages, are needed. In sum, the SEE Learning program shows evidence of promise for impacting elementary school students’ prosocial skills and competencies.

Ternary Interactions Balance Enabled Sequential Assembly toward the Synthesis of Hierarchically Mesoporous Metal Hydroxide Nanoparticles

Cross-attention guided discriminative feature selection for robust point cloud domain generalization

In recent years, deep learning networks have been widely employed for point cloud classification. However, discrepancies between training and testing scenarios often result in erroneous predictions. Domain generalization (DG) aims to achieve high classification accuracy in unseen scenarios without requiring additional training. Although current DG methodologies effectively employ data augmentation and representation learning, they inadvertently neglect a key component: discriminative feature selection, which we identify as a crucial missing element for achieving robust domain generalization. To fully leverage the geometric features of point clouds, we propose a novel domain generalization method that emphasizes transferring contextual information to improve generalization performance for 3D point clouds. Our method projects the point cloud into multiple views and employs a 2D adaptive feature extractor to capture and aggregate weighted semantic features, while leveraging the DGCNN network to extract 3D spatial geometric features. Additionally, we incorporate an attention mechanism to fuse 2D semantic features with 3D geometric features, facilitating the selection of discriminative features from point clouds. The experiments demonstrate that our method outperforms state-of-the-art methods in both multi-source and single-source tasks, achieving superior generalization performance.

Feasibility and acceptability of collecting passive phone usage and sensor data via Apple SensorKit

Privacy is a growing concern in mobile health research, particularly regarding passive data. Apple SensorKit provides a novel platform for collecting phone and wearable usage and sensor data, however the acceptability and feasibility of collecting these sensitive data to research subjects remain unknown. To address this gap, we piloted the SensorKit platform as part of the longitudinal Intern Health Study. Unlike prior research on digital privacy, which has often relied on small samples, this study leverages a large and demographically diverse cohort of US medical residents to explore racial and ethnic differences in the acceptability of passive sensor data collection. Findings demonstrate that successful enrollment and retention rates can be achieved in a longitudinal e-Cohort study that collects SensorKit data, however lower opt-in rates among racial minorities suggest the need for further evaluation of the equity implications around specific data types in mobile health research.

Simulation Evidence of Nanobubble Clusters of Gas in Water: A Nanoscale Solvation Mechanism

Computationally accelerated identification of P-glycoprotein inhibitors

Overexpression of the polyspecific efflux transporter, P-glycoprotein (P-gp, MDR1, ABCB1), is a major mechanism by which cancer cells acquire multidrug resistance (MDR), the resistance to diverse chemotherapeutic drugs. Inhibiting drug transport by P-gp can resensitize cancer cells to chemotherapy, but there are no P-gp inhibitors available to patients. Clinically unsuccessful P-gp inhibitors tend to bind at the pump’s transmembrane drug binding domains and are often P-gp transport substrates, resulting in lowered intracellular concentration of the drug and altered pharmacokinetics. In prior work, we used computationally accelerated drug discovery to identify novel P-gp inhibitors that target the pump’s cytoplasmic nucleotide binding domains. Our first-draft study provided conclusive evidence that the nucleotide binding domains of P-gp are viable targets for drug discovery. Here we develop an enhanced, computationally accelerated drug discovery pipeline that expands upon our prior work by iteratively screening compounds against multiple conformations of P-gp with molecular docking. Targeted molecular dynamics simulations with our homology model of human P-gp were used to generate docking receptors in conformations mimicking a putative drug transport cycle. We offset the increased computational complexity using custom Tanimoto chemical datasets, which maximize the chemical diversity of ligands screened by docking. Using our expanded, virtual-assisted pipeline, we identified nine novel P-gp inhibitors that reverse MDR in two types of P-gp overexpressing human cancer cell lines, reflecting a 13.4% hit rate. Of these inhibitors, all were non-toxic to non-cancerous human cells, and six were not likely to be transport substrates of P-gp. Our novel P-gp inhibitors are chemically diverse and are good candidates for lead optimization. Our results demonstrate that the nucleotide binding domains of P-gp are an underappreciated target in the effort to reverse P-gp-mediated multidrug resistance in cancer.

Do organisms need an impact factor? Citations of key biological resources including model organisms reveal usage patterns and impact

Research resources like transgenic animals and antibodies are the workhorses of biomedicine, enabling investigators to relatively easily study specific disease conditions. As key biological resources, transgenic animals and antibodies are often validated, maintained, and distributed from university-based stock centers. As these centers heavily rely on grant funding, it is critical that they are cited by investigators so that usage can be tracked. However, unlike systems for tracking the impact of papers, the conventions and systems for tracking key resource usage and impact lag. Previous studies have shown that about 50% of the resources are not findable, making the studies they support irreproducible, but also makes tracking resources difficult. The RRID (Research Resource Identifiers) project is filling this gap by working with journals and resource providers to improve citation practices and to track the usage of these key resources. Here, we reviewed 10 years of citation practices for five university based stock centers, characterizing each reference into two broad categories: findable (authors could use the RRID, stock number, or full name) and not findable (authors could use a nickname or a common name that is not unique to the resource). The data revealed that when stock centers asked their communities to cite resources by RRID, in addition to helping stock centers more easily track resource usage by increasing the number of RRID papers, authors shifted from citing resources predominantly by nickname (~50% of the time) to citing them by one of the findable categories (~85%) in a matter of several years. In the case of one stock center, the MMRRC, the improvement in findability is also associated with improvements in the adherence to NIH rigor criteria, as determined by a significant increase in the Rigor and Transparency Index for studies using MMRRC mice. From these data, it was not possible to determine whether outreach to authors or changes to stock center websites drove better citation practices, but findability of research resources and rigor adherence were improved.

Organoarsine Metal–Organic Framework as a Solid-State Ligand for Rhodium(I) Olefin Hydroformylation Catalysis

Modulation of the post-auricular reflex in response to social and CT-optimal touch

The pleasantness perception of CT-optimal touch is usually assessed with subjective and explicit measures. As these can be prone to biases, it is important to develop implicit measures as well. The vestigial post-auricular muscle reflex (PAR) might be a good candidate, given its sensitivity to pleasant visual and auditory stimuli. As such, we investigated if the PAR can also be modulated by CT-optimal touch. We additionally compared how the PAR responds to social and robotic touch and conducted control experiments to replicate the reflex’s specific sensitivity to primary rewards. The sample consisted of 43 non-clinical participants. PAR responses were recorded while participants were touched by an experimenter and a robot, with a velocity of 3 cm/s (CT-optimal touch) and 18 cm/s (CT non-optimal touch). After each trial, participants also subjectively rated the pleasantness of the touch. Although the results revealed that CT-optimal touch was subjectively perceived to be more pleasant than CT non-optimal touch, it did not result in a potentiation of the PAR. Interestingly, social touch was subjectively perceived to be more pleasant than robotic touch and potentiated the PAR. The control experiments confirmed that the PAR is particularly modulated by primary (food, erotica), and not secondary (adventure, cuteness, monetary) rewards. While additional research is needed to further investigate the relation between the PAR and CT-optimal touch, the current results do already suggest that this reflex responds to the primary reward value of social touch.

Co-assembly of Covalent Organic Framework Particles into Binary Ordered Superstructures

Tracking Enterobacteria, microbiomes, and antibiotic resistance genes from waste to soil with repeated compost applications

The dissemination of antibiotic resistant bacteria (ARB) and genes is one factor responsible for the increasing antibiotic resistance and the environment plays a role in resistance spread. Animal excreta can contribute to the contamination of the environment with ARBs and antibiotics and in some cases, environmental bacteria under antibiotic pressure may acquire antibiotic resistance genes (ARGs) from ARBs by horizontal gene transfer. In Guadeloupe, a French overseas department, organic amendments derived from human and animal waste are widely used in soil fertilization, but their contribution to antibiotic resistance remains unknown. The objective of this study was to evaluate the impact of composting animal and human raw waste and the repeated application of their derived-composts, on the fate of ARGs and antibiotic resistant Enterobacteria, for the first time, in tropical soils of Guadeloupe used for vegetable production. An unculturable approach was used to characterize the bacterial community composition and ARG content from raw waste to composts. A cultivable approach was used to enumerate Enterobacteria, and resistant isolates were further characterized phenotypically and genotypically. Based on this original approach, we demonstrated that the raw poultry droppings exhibited a depletion of Escherichia and Shigella populations during the composting treatment, which was corroborated by the results on the culturable resistant Enterobacteria. Significant differences in the abundance of ARGs were also observed, with some gene levels increasing or decreasing after composting. In addition, other bacterial genera potentially involved in the spread of antimicrobial resistance were identified. Taken together, these results demonstrate that successive applications of raw waste-derived-composts from green waste, sewage sludge, and poultry droppings reshape the Enterobacterial community and influences the abundance of ARGs, with some gene levels increasing or decreasing, in Guadeloupe’s tropical vegetable production soils.

Carbon Reduction Powered by Natural Electrochemical Gradients under Submarine Hydrothermal Vent Conditions

Abstract Energy metabolism at the emergence of life has been the topic of intense theoretical and experimental study. Alkaline hydrothermal vents (AHVs) may have facilitated energy transfer and carbon fixation at life’s emergence. Specifically, pH separation across vent walls could have been the forerunner to pH separation across cell membranes, with inorganic barriers containing [Ni-]FeS minerals as precursors of metalloenzymes in potentially ancient biological reductive acetyl-CoA Wood–Ljungdahl (WL) and other metabolic pathways. We previously demonstrated pH-gradient-dependent reduction of CO2 to formate by H2 in AHV interface conditions. Here, we address the same problem of CO2 reduction using a macroscale reactor with minerals synthesized via protocols meant to mimic the natural processes of hydrothermal chimney formation. This reactor also allowed us to probe more variables and explore longer experimentation time frames. These results elucidate how different aspects of the hydrothermal–vent interface (e.g., different minerals and/or temperature gradients) affect the observed CO2 electrochemical reduction as well as the flow of electrons under passive vs induced currents and potentials. Using experimental simulations and electrochemistry techniques, we detected two key steps of the WL pathway (CO2 to formic acid and the formation of acetic acid). We explored effects of Ni incorporation in the mineral catalyst, as well as temperature and the effects of these variables on the production of formate. Currents as small as 10 nanoamps to 10 microamps were enough to efficiently carry out CO2 reduction. In this work, we electrochemically explore energy protometabolism in vent–ocean interfaces, specifically focusing on [Ni-]FeS minerals as precursors of metalloenzymes.

Complex intervention based on protective factors to improve resilience for gastric cancer patients: Mixed-methods process evaluation protocol

Background Gastric cancer represents a global health burden, with patients often experiencing significant psychological distress due to various treatments. Resilience, the ability to adapt positively to challenges, is crucial for the mental and physical well-being of gastric cancer patients. Despite its importance, there are still gaps in research aimed at enhancing resilience. This paper presents a process evaluation protocol embedded within a complex intervention aimed at enhancing resilience in gastric cancer patients during chemotherapy. The protocol aims to understand the implementation process, mechanisms, influencing factors, and outcomes. Methods The process evaluation will use a mixed-methods approach. The Consolidated Framework for Implementation Research (CFIR) and the RE-AIM framework were chosen to qualitatively identify the factors that influence intervention implementation and the outcomes of implementation, including the reach, efficacy, adoption and maintenance. The implementation process will be assessed based on the UK Medical Research Council’s guidance on evaluating complex interventions. The fidelity, dose and adherence will be analysed through the goal achievement log book, and the mechanisms of intervention implementation will be assessed using parallel latent growth curve model with quantitative information. Semi-structured interviews will be conducted with intervention staff and participants, data from the goal achievement log book will be analyzed, and data from the primary and secondary outcome indicators will be analyzed for parallel latent growth curve parameters. Discussion This study outlines a process evaluation protocol for a complex intervention. The protocol aims to further validate the effectiveness of the intervention and guide the development of more comprehensive resilience strategies, thus promoting broader application among other chronic disease patient populations. Trial registration The trial has been prospectively registered on 11 July 2023; ChiCTR2300073466.

Safety of antidepressants commonly used in 6–17-year-old children and adolescents: A disproportionality analysis from 2014–2023 on the basis of the FAERS database

Background Depression is a common mental disorder in children and adolescents, and antidepressants are widely used for treatment. This study aimed to explore and analyze adverse events (AEs) associated with antidepressant use in this population, providing insights for safety assessment. Methods This study extracted AE reports from the US FDA Adverse Event Reporting System (FAERS) for children and adolescents aged 6–17 years from 2014–2023, with fluoxetine, escitalopram, and sertraline as the primary suspected drugs. The study used the International Dictionary of Medical Terminology (MedDRA) to encode and classify AEs, and employed the reporting odds ratio (ROR) and proportional reporting ratio (PRR) methods for data mining. Results The FAERS database included 9,845 AE reports involving fluoxetine, escitalopram, and sertraline among children and adolescents aged 6–17 years. After removing duplicates, the analysis yielded 1,604, 352, and 571 AEs for fluoxetine, escitalopram, and sertraline, respectively. The study population demonstrated a sex distribution with approximately twice as many female patients as male patients, with most patients aged 12–17 years. At the system organ class (SOC) level, the AEs predominantly involved psychiatric disorders and nervous system disorders. Within the psychiatric disorders category at the high level group term (HLGT) level, the most frequently reported AE signals across all three medications were suicidal and self-injurious behaviors (not elsewhere classified, hereinafter referred to as NEC) and anxiety disorders and symptoms; For nervous system disorders, the predominant AE signals were neurological disorders (NEC) and movement disorders (including parkinsonism). At the Preferred Term (PT) level, the three antidepressants demonstrated similar AEs, including various suicidal and self-injurious behaviors, intentional overdose, neurological disorders (including serotonin syndrome, extravertebral reactions, etc) and prolonged QT. The typical AEs of fluoxetine included decreased appetite, insomnia, and urinary retention. Escitalopram was associated with additional AEs of sexual dysfunction and toxic epidermal necrolysis, whereas sertraline demonstrated unique associations with headache and rhabdomyolysis. Conclusion This study may offer further evidence regarding AEs associated with commonly prescribed antidepressants in children and adolescents. Overall, the findings are mostly consistent with the AEs recorded in the packaging instructions and previous reports. However, the study also identified previously unreported AEs and highlighted variations in the AE profiles across different demographic groups. As the causal relationships between these medications and the observed AEs remain to be fully elucidated, additional research is warranted to confirm these findings.