Ultrasound-Targeted Microbubble Destruction Enhances the Inhibitory Effect of Sonodynamic Therapy against Hepatocellular Carcinoma.

: To assess the anticancer effect of microbubbles (MBs) in combination with sinoporphyrin sodium (DVDMS)-mediated sonodynamic therapy (SDT) for the in vitro and in vivo treatment of hepatocellular carcinoma (HCC). : HepG2 cells were used for in vitro experiments. Reactive oxygen species (ROS) production was detected using 2',7'-dichlorodihydrofluorescein diacetate and singlet oxygen sensor green in vitro and in solution, respectively.

Cellular Feimin enhances exercise performance by suppressing muscle thermogenesis.

Exercise can rapidly increase core body temperature, and research has indicated that elevated internal body temperature can independently contribute to fatigue during physical activity. However, the precise mechanisms responsible for regulating thermogenesis in muscles during exercise have remained unclear. Here, we demonstrate that cellular Feimin (cFeimin) enhances exercise performance by inhibiting muscle thermogenesis during physical activity.

Quantitative Histopathology Analysis Based on Label-free Multiphoton Imaging for Breast Cancer Diagnosis and Neoadjuvant Immunotherapy Response Assessment.

Accurate diagnosis and assessment of breast cancer treatment responses are critical challenges in clinical practice, influencing patient treatment strategies and ultimately long-term prognosis. Currently, diagnosing breast cancer and evaluating the efficacy of neoadjuvant immunotherapy (NAIT) primarily rely on pathological identification of tumor cell morphology, count, and arrangement. However, when tumors are small, the tumors and tumor beds are difficult to detect; relying solely on tumor cell identification may lead to false negatives.

Random Illumination Microscopy: faster, thicker, and aberration-insensitive.

The Extended Depth of Field (EDF) approach has been combined with Random Illumination Microscopy (RIM) to realize aberration-insensitive, fast super-resolution imaging with extended depth, which is a promising tool for dynamic imaging in larger and thicker live cells and tissues.

Targeted LNPs deliver IL-15 superagonists mRNA for precision cancer therapy.

Interleukin-15 (IL-15) emerges as a promising immunotherapeutic candidate, but the therapeutic utility remains concern due to the unexpected systematic stress. Here, we propose that the mRNA lipid nanoparticle (mRNA-LNP) system can balance the issue through targeted delivery to increase IL-15 concentration in the tumor area and reduce leakage into the circulation. In the established Structure-driven TARgeting (STAR) platform, the LNP and LNP can effectively and selectively deliver optimized IL-15 superagonists mRNAs to local and lungs, respectively, in relevant tumor models.

Precise identification of somatic and germline variants in the absence of matched normal samples.

Somatic variants play a crucial role in the occurrence and progression of cancer. However, in the absence of matched normal controls, distinguishing between germline and somatic variants becomes challenging in tumor samples. The existing tumor-only genomic analysis methods either suffer from limited performance or insufficient interpretability due to an excess of features.

Investigating ocular biomarkers and differential diagnosis of Alzheimer's disease and vascular cognitive impairment based on multimodal imaging.

Significance: The eye can be used as a potential monitoring window for screening, diagnosis, and monitoring of neurological diseases. Alzheimer's disease (AD) and vascular cognitive impairment (VCI) are common causes of cognitive impairment and may share many similarities in ocular signs. Multimodal ophthalmic imaging is a technology to quantify pupillary light reaction, retinal reflectance spectrum, and hemodynamics.

A Modular Engineered DNA Nanodevice for Precise Profiling of Telomerase RNA Location and Activity.

Increased telomerase activity has been considered as a conspicuous sign of human cancers. The catalytic cores of telomerase involve a reverse transcriptase and the human telomerase RNA (hTR). However, current detection of telomerase is largely limited to its activity at the tissue and single-cell levels.

Action Potential Firing Patterns Regulate Dopamine Release via Voltage-Sensitive Dopamine D2 Autoreceptors in Mouse Striatum In Vivo.

Dopamine (DA) in the striatum is vital for motor and cognitive behaviors. Midbrain dopaminergic neurons generate both tonic and phasic action potential (AP) firing patterns in behavior mice. Besides AP numbers, whether and how different AP firing patterns per se modulate DA release remain largely unknown.

Artificial intelligence-enabled discovery of a RIPK3 inhibitor with neuroprotective effects in an acute glaucoma mouse model.

Background: Retinal ganglion cell (RGC) death caused by acute ocular hypertension is an important characteristic of acute glaucoma. Receptor-interacting protein kinase 3 (RIPK3) that mediates necroptosis is a potential therapeutic target for RGC death. However, the current understanding of the targeting agents and mechanisms of RIPK3 in the treatment of glaucoma remains limited.

An integrative data-driven model simulating C. elegans brain, body and environment interactions.

The behavior of an organism is influenced by the complex interplay between its brain, body and environment. Existing data-driven models focus on either the brain or the body-environment. Here we present BAAIWorm, an integrative data-driven model of Caenorhabditis elegans, which consists of two submodels: the brain model and the body-environment model.

RNA-programmable cell type monitoring and manipulation in the human cortex with CellREADR.

Reliable and systematic experimental access to diverse cell types is necessary for understanding the neural circuit organization, function, and pathophysiology of the human brain. Methods for targeting human neural populations are scarce and currently center around identifying and engineering transcriptional enhancers and viral capsids. Here we demonstrate the utility of CellREADR, a programmable RNA sensor-effector technology that couples cellular RNA sensing to effector protein translation, for accessing, monitoring, and manipulating specific neuron types in human cortical tissues.

Diagnosis of Fibrotic Interstitial Lung Diseases Based on the Combination of Label-Free Quantitative Multiphoton Fiber Histology and Machine Learning.

Interstitial lung disease (ILD), characterized by inflammation and fibrosis, often suffers from low diagnostic accuracy and consistency. Traditional hematoxylin and eosin (H&E) staining primarily reveals cellular inflammation with limited detail on fibrosis. To address these issues, we introduce a pioneering label-free quantitative multiphoton fiber histology (MPFH) technique that delineates the intricate characteristics of collagen and elastin fibers for ILD diagnosis.

Mitochondrial dynamics govern whole-body regeneration through stem cell pluripotency and mitonuclear balance.

Tissue regeneration is a complex process involving large changes in cell proliferation, fate determination, and differentiation. Mitochondrial dynamics and metabolism play a crucial role in development and wound repair, but their function in large-scale regeneration remains poorly understood. Planarians offer an excellent model to investigate this process due to their remarkable regenerative abilities.

π-HuB: the proteomic navigator of the human body.

The human body contains trillions of cells, classified into specific cell types, with diverse morphologies and functions. In addition, cells of the same type can assume different states within an individual's body during their lifetime. Understanding the complexities of the proteome in the context of a human organism and its many potential states is a necessary requirement to understanding human biology, but these complexities can neither be predicted from the genome, nor have they been systematically measurable with available technologies.

Self-improving generative foundation model for synthetic medical image generation and clinical applications.

In many clinical and research settings, the scarcity of high-quality medical imaging datasets has hampered the potential of artificial intelligence (AI) clinical applications. This issue is particularly pronounced in less common conditions, underrepresented populations and emerging imaging modalities, where the availability of diverse and comprehensive datasets is often inadequate. To address this challenge, we introduce a unified medical image-text generative model called MINIM that is capable of synthesizing medical images of various organs across various imaging modalities based on textual instructions.

A cellular triad for linking cardiac niche to regeneration.

Cardiovascular disease is the leading cause of mortality with very limited therapeutic interventions, thus holding great hope for cardiac regenerative medicine. A recent work from Martin's laboratory reports their identification of a fetal-like cardiomyocyte progenitor, adult cardiomyocyte type 2 (aCM2), and its potential interactions with C3 cardiac fibroblasts and C3ar1 macrophages to form a regenerative cellular triad, which is only present in the regenerative heart models, YAP5SA-expressing adult hearts and neonatal hearts. The complement signaling is essential for cellular interactions in this regenerative triad.

A 3D bioprinted adhesive tissue engineering scaffold to repair ischemic heart injury.

Adhesive tissue engineering scaffold (ATES) devices can be secured on tissues by relying on their intrinsic adhesive properties, hence, avoiding the complications such as host tissue/scaffold damage that are associated with conventional scaffold fixation methods like suturing or bioglue. This study introduces a new generation of three-dimensional (3D) bioprinted ATES systems for use as cardiac patches to regenerate the adult human heart. Tyramine-modified methacrylated hyaluronic acid (HAMA-tyr), gelatin methacrylate (GelMA), and gelatin were used to create the hybrid bioink formulation with self-adhesive properties.

How Do DNA Molecular Springs Modulate Protein-Protein Interactions: Experimental and Theoretical Results.

Deoxyribonucleic acid (DNA) nanomachines have been widely exploited in enzyme activity regulation, protein crystallization, protein assembly, and control of the protein-protein interaction (PPI). Yet, the fundamental biophysical framework of DNA nanomachines in the case of regulating protein-protein interactions remains elusive. Here, we established a DNA nanospring-mCherry model with mCherry homodimers of different .

Ultrasound Control of Genomic Regulatory Toolboxes for Cancer Immunotherapy.

There remains a critical need for the precise control of CRISPR (clustered regularly interspaced short palindromic repeats)-based technologies. Here, we engineer a set of inducible CRISPR-based tools controllable by focused ultrasound (FUS), which can penetrate deep and induce localized hyperthermia for transgene activation. We demonstrate the capabilities of FUS-inducible CRISPR, CRISPR activation (CRISPRa), and CRISPR epigenetic editor (CRISPRee) in modulating the genome and epigenome.

16-channel sleeve antenna array based on passive decoupling method at 14 T.

At ultra-high fields, especially at 14 T, head coil arrays face significant challenges with coupling between elements. Although passive decoupling methods can reduce this coupling, the decoupling elements can cause destructive interference to the RF field of the head array, thus reducing the B efficiency. The B loss due to this effect can be even higher than that due to inter-element coupling.

Accurate and transferable drug-target interaction prediction with DrugLAMP.

Motivation: Accurate prediction of drug-target interactions (DTIs), especially for novel targets or drugs, is crucial for accelerating drug discovery. Recent advances in pretrained language models (PLMs) and multi-modal learning present new opportunities to enhance DTI prediction by leveraging vast unlabeled molecular data and integrating complementary information from multiple modalities.

Results: We introduce DrugLAMP (PLM-assisted multi-modal prediction), a PLM-based multi-modal framework for accurate and transferable DTI prediction.