Antimicrobial Peptides and Their Mimetics: Promising Candidates of Next-Generation Therapeutic Agents Combating Multidrug-Resistant Bacteria.

The increasing morbidity and mortality caused by multidrug-resistant bacteria alerts human beings to the fact that conventional antibiotics are no longer reliable and effective alternatives are imperatively needed. Owing to wide range of sources, diverse structures, and unique mode of action, antimicrobial peptides have been highly anticipated and extensively studied in recent years. Besides, the integration of artificial intelligence helps researchers gain access to the vast unexplored chemical space, which opens more opportunities for the optimization and design of novel structures.

Correction: Zhang et al. Interactions of Self-Assembled Polysaccharide Nanoparticles with Bovine Serum Albumin and Biodistribution of Its Docetaxel-Loaded Nanoparticles. 2019, , 43.

In the original publication [...

Humans Continue to Outperform Large Language Models in Complex Clinical Decision-Making: A Study with Medical Calculators.

Although large language models (LLMs) have been assessed for general medical knowledge using medical licensing exams, their ability to effectively support clinical decision-making tasks, such as selecting and using medical calculators, remains uncertain. Here, we evaluate the capability of both medical trainees and LLMs to recommend medical calculators in response to various multiple-choice clinical scenarios such as risk stratification, prognosis, and disease diagnosis. We assessed eight LLMs, including open-source, proprietary, and domain-specific models, with 1,009 question-answer pairs across 35 clinical calculators and measured human performance on a subset of 100 questions.

Demystifying Large Language Models for Medicine: A Primer.

Large language models (LLMs) represent a transformative class of AI tools capable of revolutionizing various aspects of healthcare by generating human-like responses across diverse contexts and adapting to novel tasks following human instructions. Their potential application spans a broad range of medical tasks, such as clinical documentation, matching patients to clinical trials, and answering medical questions. In this primer paper, we propose an actionable guideline to help healthcare professionals more efficiently utilize LLMs in their work, along with a set of best practices.

CLIPA protein pairs function as cofactors for prophenoloxidase activation in Anopheles gambiae.

Insect prophenoloxidases (proPO) are activated during immune responses by a proPO activating protease (PAP) in the presence of a high molecular weight cofactor assembled from serine protease homologs (SPH) that lack proteolytic activity. PAPs and the SPHs have a similar architecture, with an amino-terminal clip domain and a carboxyl-terminal protease domain. The SPHs belong to CLIPA subfamily of SP-related proteins.

Multifunctional NO supramolecular nanomedicine for thrombus risk reduction and intimal hyperplasia inhibition.

Cardiovascular diseases (CVDs) are the foremost cause of mortality worldwide, with incidence and mortality rates persistently climbing despite extensive research efforts. Innovative therapeutic approaches are still needed to extend patients' lives and preserve their health. In the present study, novel supramolecular nanomedicine with both nitric oxide (NO) and antioxidant releasing ability was developed to enhance therapeutic efficacy against vascular injuries.

Leveraging Professional Radiologists' Expertise to Enhance LLMs' Evaluation for AI-generated Radiology Reports.

In radiology, Artificial Intelligence (AI) has significantly advanced report generation, but automatic evaluation of these AI-produced reports remains challenging. Current metrics, such as Conventional Natural Language Generation (NLG) and Clinical Efficacy (CE), often fall short in capturing the semantic intricacies of clinical contexts or overemphasize clinical details, undermining report clarity. To overcome these issues, our proposed method synergizes the expertise of professional radiologists with Large Language Models (LLMs), like GPT-3.

Improving Retrieval-Augmented Generation in Medicine with Iterative Follow-up Questions.

The emergent abilities of large language models (LLMs) have demonstrated great potential in solving medical questions. They can possess considerable medical knowledge, but may still hallucinate and are inflexible in the knowledge updates. While Retrieval-Augmented Generation (RAG) has been proposed to enhance the medical question-answering capabilities of LLMs with external knowledge bases, it may still fail in complex cases where multiple rounds of information-seeking are required.

Understanding Fatigue, Insomnia, and COVID-19 PTSS Among Mainland Chinese During Initial Post-Zero-COVID Infection Wave: A Multi-Group Analysis.

In early 2023, China experienced its first widespread COVID-19 outbreak after a policy shift. This study examines the relationship between fatigue and COVID-19-related post-traumatic stress symptoms (PTSS) in infected and uninfected individuals, exploring the potential mediating role of insomnia symptoms. An online survey of 5953 Chinese participants was conducted from 10 to 16 January 2023.

Confined Magnetization at the Sublattice-Matched Ruthenium Oxide Heterointerface.

Creating a heterostructure by combining two magnetically and structurally distinct ruthenium oxides is a crucial approach for investigating their emergent magnetic states and interactions. Previously, research has predominantly concentrated on the intrinsic properties of the ferromagnet SrRuO and recently discovered altermagnet RuO solely. Here, the study engineers an ultrasharp sublattice-matched heterointerface using pseudo-cubic SrRuO and rutile RuO, conducting an in-depth analysis of their spin interactions.

Cardamonin Attenuates Myocardial Ischemia/Reperfusion-Induced Ferroptosis Through Promoting STAT3 Signaling.

Objective: Ferroptosis is intricately associated with the pathophysiology processes of myocardial ischemia. Cardamonin (CAR) has been shown to provide significant protection against tissue damage due to multiple ischemia/reperfusion. This study aimed to examine the cardioprotective properties of CAR in myocardial ischemia/reperfusion injury (MIRI) and provide insights into the possible mechanisms involved.

Matching patients to clinical trials with large language models.

Patient recruitment is challenging for clinical trials. We introduce TrialGPT, an end-to-end framework for zero-shot patient-to-trial matching with large language models. TrialGPT comprises three modules: it first performs large-scale filtering to retrieve candidate trials (TrialGPT-Retrieval); then predicts criterion-level patient eligibility (TrialGPT-Matching); and finally generates trial-level scores (TrialGPT-Ranking).

Simultaneous inhibition of heat shock proteins and autophagy enhances radiofrequency ablation of hepatocellular carcinoma.

Radiofrequency ablation (RFA) is a commonly used minimally invasive treatment for hepatocellular carcinoma (HCC). However, incomplete radiofrequency ablation (iRFA) promotes tumor progression and metastasis. There is an urgent need to develop innovative strategies to enhance the efficacy of iRFA.

Synergistic wall digestion and cuproptosis against fungal infections using lywallzyme-induced self-assembly of metal-phenolic nanoflowers.

Fungi are very common infectious pathogens, which may cause invasive and potentially life-threatening infections. However, the efficacy of antifungal medications remains limited. Herein, a Cu-phenolic nanoflower is designed to combat fungal infections by combining cuproptosis and cell wall digestion.

Unmasking and quantifying racial bias of large language models in medical report generation.

Background: Large language models like GPT-3.5-turbo and GPT-4 hold promise for healthcare professionals, but they may inadvertently inherit biases during their training, potentially affecting their utility in medical applications. Despite few attempts in the past, the precise impact and extent of these biases remain uncertain.

Nanomaterial-based therapeutics for enhanced antifungal therapy.

The application of nanotechnology in antifungal therapy is gaining increasing attention. Current antifungal drugs have significant limitations, such as severe side effects, low bioavailability, and the rapid development of resistance. Nanotechnology offers an innovative solution to address these issues.

Postoperative PFME versus PFME alone for moderate SUI in pre-menopause women and influencing factors: a comparative effectiveness study.

Purpose: To explore the effectiveness of sling surgery followed by pelvic floor muscle exercises (PFME) or PFME alone for moderate stress urinary incontinence (SUI) in women and its influencing factors.

Methods: This is a prospective observational cohort study investigating whether sling surgery or PFME is preferred for pre-menopause women with moderate uncomplicated SUI. Those who received PFME alone or sling surgery were divided to PT or TVT group, respectively.

Removable Photocatalysis Microneedle Reactor for Carbon Monoxide Delivery to Enhance Chemosensitization.

Carbon monoxide (CO) has emerged as a promising therapeutic agent, yet ensuring safe and precise CO delivery remains challenging. Here, we report a removable hydrogel-forming microneedle (MN) reactor for CO delivery via photocatalysis, with an emphasis on chemosensitization. Upon application, body fluids absorbed by the MNs dissolve the effervescent agents, leading to the generation of carbon dioxide (CO) and triggering the release of the chemotherapeutics cisplatin.

Tumor microenvironment-modulated nanoparticles with cascade energy transfer as internal light sources for photodynamic therapy of deep-seated tumors.

Photodynamic therapy (PDT) is an appealing modality for cancer treatments. However, the limited tissue penetration depth of external-excitation light makes PDT impossible in treating deep-seated tumors. Meanwhile, tumor hypoxia and intracellular reductive microenvironment restrain the generation of reactive oxygen species (ROS).