Browse Articles

<i>s</i>-Block Metal-Lanthanide Bonding: Direct Comparison of Mg–Yb and Mg–Ca Complexes

Investigating long-term risk of aortic aneurysm and dissection from fluoroquinolones and the key contributing factors using machine learning methods

Terphenylthiolate-Ligated Lanthanide Terminal Methyl Complexes Form Crystallographically Characterizable Terminal Acyls and Trimethylcyclopropanetriolates from Carbon Monoxide

Association between body roundness index and incidence of type 2 diabetes in a population-based cohort study

Charging of Single Molecules Mediated by the Quantum Phase of Molecular Orbitals

Efficient detection of gastric cancer biomarkers on functionalized carbon nanoribbons using DFT analysis

Spin Filtering with Surface-Active Helicene- and Twistacene-Based Perylene Diimides

Barriers to the widespread adoption of diagnostic artificial intelligence for preventing antimicrobial resistance

Abstract Currently, antimicrobial resistance (AMR) poses a major public health challenge. The emergence of AMR, which significantly threatens public health, is primarily due to the overuse of antimicrobial agents. This study explored the possibility that the ethical dilemmas inherent in the context of AMR may hinder the adoption of diagnostic artificial intelligence (AI). We conducted a web survey across eight countries/areas to assess public preference between two hypothetical AI types: one prioritizing individual health and the other considering the global AMR threat. Our results revealed a societal preference for the utilization of both AI types, reflecting a conflict between recognizing the significance of AMR and the desire for individualized treatment. Interestingly, the survey indicated significant gender and age differences in AI preferences, and the majority of respondents opposed the idea of AI standardization in treatment. These findings highlight the challenges of incorporating AI into public health and the necessity of considering public sentiment in addressing global health issues such as AMR.

Nucleation and Growth of Monodisperse CdTe and CdTe/ZnSe Core/shell Nanocrystals: Roles of Cationic Precursors, Ligands, and Solvents

Staphylococcus saprophyticus prevents skin damage by inhibiting Staphylococcus aureus quorum sensing

Spaser Nanoprobes Family for Narrow-Band Multiplexed Cell Imaging

Fish consumption and gastric cancer within the Stomach cancer Pooling (StoP) Project

Selective Aliphatic Aldimine Formation and Stabilization by a Hydrophobic Capsule in Water

Author Correction: Population structure and identification of genomic regions associated with productive traits in five Italian beef cattle breeds

Resolving Complex K–Pt–Sn Interactions in PtSn@K-MFI Catalysts for Alkane Dehydrogenation

Author Correction: Next generation sequencing uncovers multiple miRNAs associated molecular targets in gallbladder cancer patients

Graphene-Based Glucose Sensors with an Attomolar Limit of Detection

Hypertension and associated factors among patients with diabetes mellitus attending a follow-up clinic in central Ethiopia

Bioinspired Nucleic Acid-Based Bandpass Filters and Their Concentration-Adaptive Functions

The effect of cortisol in early pregnancy on postpartum depressive symptoms

Abstract The first months after childbirth are a tremendous challenge for women and, consequently, a time when women’s mental health problems often arise. Knowledge of the prenatal predictors of these problems is of fundamental importance in preventing them. This study aimed to test whether first trimester hair cortisol influenced maternal postpartum depressive symptoms. The women (N = 75) were tested twice: in the first trimester of pregnancy and within three months after giving birth. In the first trimester, they had hair samples taken and were examined using a sociodemographic survey and questionnaires: the Edinburgh Postnatal Depression Scale (EPDS), the Perceived Stress Scale (PSS-10), and the Zimbardo Time Perspective Inventory. After delivery, women completed a survey about the course of delivery and their child’s health, EPDS, and PSS-10. Low hair cortisol concentration in the first trimester was a predictor of a high level of postpartum depressive symptoms. This relationship was mediated by fatalistic time perspective. The results suggest that low hair cortisol concentration in the first trimester of pregnancy indicates a high probability of postpartum depression, and that low levels of cortisol may be associated with passivity, a sense of lack of control, and helplessness.