Polarization-dependent control of ionization pathways in atomic strong-field nonsequential double ionization.

Utilizing a classical ensemble model (CEM), we have studied the rescattering behavior of quasi-free tunneling electron and correlation dynamics of electron pair during nonsequential double ionization (NSDI) of Xe atoms induced by a counter-rotating, two-color, elliptically polarized (TCEP) laser field. Our numerical results reveal that the momentum of the first tunneling electron is predominantly located in the third quadrant of momentum spectrum, whereas the momentum spectrum of the second electron presents a triangular structure along the direction of the negative vector potential of driving field. This phenomenon occurs because the first electron has greater emission kinetic energy than the second one, rendering the latter more sensitive to the influence exerted by the electric field vector potential.

Accelerating clinical evidence synthesis with large language models.

Clinical evidence synthesis largely relies on systematic reviews (SR) of clinical studies from medical literature. Here, we propose a generative artificial intelligence (AI) pipeline named TrialMind to streamline study search, study screening, and data extraction tasks in SR. We chose published SRs to build TrialReviewBench, which contains 100 SRs and 2,220 clinical studies.

A foundation model for human-AI collaboration in medical literature mining.

Systematic literature review is essential for evidence-based medicine, requiring comprehensive analysis of clinical trial publications. However, the application of artificial intelligence (AI) models for medical literature mining has been limited by insufficient training and evaluation across broad therapeutic areas and diverse tasks. Here, we present LEADS, an AI foundation model for study search, screening, and data extraction from medical literature.

A perspective for adapting generalist AI to specialized medical AI applications and their challenges.

We introduce a framework to adapt large language models for medicine: (1) Modeling: breaking down medical workflows into manageable steps; (2) Optimization: optimizing model performance via advanced adaptations; and (3) System engineering: developing agent or chain systems. Furthermore, we describe varied use cases, such as clinical trial design, clinical decision support, and medical imaging analysis. Finally, we discuss challenges and considerations for building medical AI with LLMs.

Quasi-photonic crystals-boosted highly efficient TiCT MXene photothermal materials for untethered actuators and therapeutics.

The near-perfect internal photothermal conversion efficiency of MXene has made them ideal candidates for diverse applications. However, the photothermal performance of MXene was limited by the low optical absorption, resulting in low overall conversion efficiency and inferior heating efficacy. Herein, we proposed a facile and universal method for obtaining high-efficiency photothermal systems simply by vacuum-filtrating polytetrafluoroethylene nanoparticles (PTFE NPs) on typical photothermal materials, e.

Cerebrospinal Fluid-Derived Genomic Alterations Tracking Glioma.

Diffuse gliomas are aggressive brain tumors known for heterogeneity and frequent oncogenic mutations. Our study harnessed circulating tumor DNA (ctDNA) in cerebrospinal fluid (CSF) as a less invasive method for disease monitoring and guiding therapeutic interventions. Through targeted sequencing of ctDNA from CSF and matched blood and tumor tissue samples, we aimed to identify glioma-associated somatic alterations and DNA fragmentations.

SLIT3-mediated intratumoral crosstalk induces neuroblastoma differentiation via a spontaneous regression-like program.

Background: Neuroblastoma, the most common pediatric extracranial solid tumor, has heterogeneous clinical outcomes ranging from malignant progression to spontaneous regression. With the highest frequency of the elusive spontaneous regression, low-risk INSS Stage 4S neuroblastoma represents an ideal model for mechanistic investigation. Spontaneous regression is often accompanied by tumor differentiation, but the mechanisms underlying this process remain largely unclear.

Microneedle Arrays for Near-Infrared-Controlled Insulin Delivery Based on Thermosensitive Microgel.

Insulin delivery plays a crucial role in diabetic treatment. Regular painless administration methods are not ideal for insulin delivery due to their insufficient bioavailability and inefficiency. In this study, dissolving microneedle array patches containing a thermosensitive insulin carrier P(NIPAm-AAm) microgel (MG) and the photothermal agent MXene were prepared with drug-protected protocols for near-infrared (NIR) light-controlled painless and minimally invasive insulin delivery.

ASB7 is a negative regulator of H3K9me3 homeostasis.

The maintenance of histone H3 lysine 9 trimethylation (H3K9me3) involves the recognition of preexisting modifications by heterochromatin protein 1 (HP1), which recruits the methyltransferase suppressor of variegation 3-9 homolog 1 (SUV39H1) to methylate the adjacent newly incorporated histones, establishing a positive feedback loop. However, how this positive feedback is restricted to maintain H3K9me3 homeostasis remains largely unknown. We performed an unbiased genome-scale CRISPR-Cas9 screen and identified CUL5 E3 ubiquitin ligase as a negative regulator of H3K9me3.

An electrochromism-equipped enzymatic biofuel cell system combined with hollow microneedle array for self-powered glucose sensing in interstitial fluid.

A disposable, self-powered enzymatic biofuel cell (BFC) sensor integrated with a hollow microneedle array (HMNA) for glucose monitoring in interstitial fluid (ISF) is reported. The HMNA enables painless and minimally invasive ISF extraction. The BFC uses dehydrogenase (GDH) in conjunction with NAD, diaphorase (DI), and vitamin K (VK) serving as electron transfer mediators as the anode catalyst and Prussian blue (PB) as the electrochromic cathode.

Multifunctional Fiber Robotics with Low Mechanical Hysteresis for Magnetic Navigation and Inhaled Gas Sensing.

Recently, increasing research attention has been directed toward detecting the distribution of hazardous gases in the respiratory system for potential diagnosis and treatment of lung injury. Among various technologies, magnetic fiber robots exhibit great potential for minimally invasive surgery and in situ disease diagnosis. However, integrating magnetic fibers with functionalized sensitive materials remains challenging while preserving the miniaturized fibers' mechanical properties.

Modulation of electron correlation dynamics in atomic non-sequential double ionization by counter-rotating two-color circularly polarized laser fields.

We investigate the ultrafast electron correlation effects during non-sequential double ionization (NSDI) of argon subjected to a combined femtosecond field composed of counter-rotating two-color circularly polarized (TCCP) pulse laser using a 3D classical ensemble model (CEM). Our simulation results reveal that manipulation of the carrier-envelope phase (CEP) of the external driving field modulates the dynamical behavior of the two electrons, resulting in a notable sensitivity of their momentum distribution to the relative phase of two components of the counter-rotating TCCP field. Through inversion analysis, we uncover the capability to direct electrons toward a single direction, thereby facilitating focused ion-electron collisions on the attosecond timescale.

Clinical characteristics and prognostic analysis of patients with hydrocephalus after hypertensive cerebral haemorrhage: a retrospective case-control study.

To investigate the clinical characteristics of patients with hydrocephalus after hypertensive cerebral haemorrhage (HICH) and to analyse the relevant factors affecting the prognosis. A total of 500 patients with HICH admitted to the neurosurgery department of The First Hospital of Hebei Medical University between January 2020 and July 2024 were retrospectively analysed. The clinical data of the patients were collected, the occurrence of hydrocephalus within 3 months after discharge was followed up, and the patients were divided into the occurrence group and the non-occurrence group.

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.

A stage structured model for mosquito suppression with immigration.

The incompatible insect technique based on is a promising alternative to control mosquito-borne diseases, such as dengue fever, malaria, and Zika, which drives wild female mosquitoes sterility through a mechanism cytoplasmic incompatibility. A successful control program should be able to withstand the perturbation induced by the immigration of fertilized females from surrounding uncontrolled areas. In this paper, we formulated a system of delay differential equations, including larval and adult stages, interfered by -infected males.

Two-Dimensional Catalysts: From Model to Reality.

Two-dimensional (2D) materials have been utilized broadly in kinds of catalytic reactions due to their fully exposed active sites and special electronic structure. Compared with real catalysts, which are usually bulk or particle, 2D materials have more well-defined structures. With easily identified structure-modulated engineering, 2D materials become ideal models to figure out the catalytic structure-function relations, which is helpful for the precise design of catalysts.

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).

Therapeutic potential of plasma-treated solutions in atopic dermatitis.

Atopic Dermatitis (AD) is a prevalent inflammatory skin disease that is currently incurable. Plasma-treated solutions (PTS) (e.g.

FOXN3-AS1: A Candidate Prognostic Marker and Epigenetic Target with Immunotherapeutic Implications in Acute Myeloid Leukemia.

Aim: We focused on the FOXN3 gene and selected its antisense transcripts (FOXN3-AS1) to investigate its potential involvement in acute myeloid leukemia (AML).

Background: Several integrated multi-omics datasets have expanded the horizons of the cancer landscape. With the emergence of new high-throughput technologies, a large number of non-coding RNAs have been confirmed to be involved in the pathogenesis of different types of hematological malignancies.

Nebulized inhalation of plasma-activated water in the treatment of progressive moderate COVID-19 patients with antiviral treatment failure: a randomized controlled pilot trial.

Background: Antiviral drugs show significant efficacy in non-severe COVID-19 cases, yet there remains a subset of moderate COVID-19 patients whose pneumonia continues to progress post a complete course of treatment. Plasma-activated water (PAW) possesses anti-SARS-CoV-2 properties. To explore the potential of PAW in improving pneumonia in COVID-19 patients following antiviral treatment failure, we conducted this study.

TOX2 nuclear-cytosol translocation is linked to leukemogenesis of acute T-cell leukemia by repressing TIM3 transcription.

Nuclear factors TOX and TOX2 upregulate TIM3 expression and lead to T-cell exhaustion in malignancies. Here, we demonstrate two distinct TIM3 expression patterns (high & low) with high TOX and TOX2 levels in T-cell acute lymphoblastic leukemia (T-ALL) specimens and cell lines. However, the mechanisms regulated by TOX and TIM3 signaling in leukemogenesis are unclear.