Speech-mediated manipulation of da Vinci surgical system for continuous surgical flow.

Unlabelled: With the advent of robot-assisted surgery, user-friendly technologies have been applied to the da Vinci surgical system (dVSS), and their efficacy has been validated in worldwide surgical fields. However, further improvements are required to the traditional manipulation methods, which cannot control an endoscope and surgical instruments simultaneously. This study proposes a speech recognition control interface (SRCI) for controlling the endoscope via speech commands while manipulating surgical instruments to replace the traditional method.

Exosomal miR-6126 as a novel therapeutic target for overcoming resistance of anti-cancer effect in hepatocellular carcinoma.

Background: Hepatocellular carcinoma (HCC) stands as the sixth most prevalent cancer globally, presenting a substantial health challenge, particularly due to late-stage diagnoses that limit treatment effectiveness. Sorafenib, a multi-kinase inhibitor, is the primary chemotherapeutic agent for advanced HCC, but it only extends survival by 2-3 months. However, drug resistance remains a major clinical challenge, necessitating the exploration of new molecular mechanisms, including the role of microRNAs (miRNAs) in sorafenib resistance.

Improving forward compatibility in class incremental learning by increasing representation rank and feature richness.

Class Incremental Learning (CIL) constitutes a pivotal subfield within continual learning, aimed at enabling models to progressively learn new classification tasks while retaining knowledge obtained from prior tasks. Although previous studies have predominantly focused on backward compatible approaches to mitigate catastrophic forgetting, recent investigations have introduced forward compatible methods to enhance performance on novel tasks and complement existing backward compatible methods. In this study, we introduce effective-Rank based Feature Richness enhancement (RFR) method that is designed for improving forward compatibility.

Advanced Enrichment and Separation of Extracellular Vesicles through the Super Absorbent Polymer Nanosieves.

Extracellular vesicles (EVs) are promising therapeutic biomaterials capable of transferring their cargo molecules and external drugs to other cells in vivo and contain various biomarkers that can be used in liquid biopsies. The clinical application of EVs requires an efficient EV enrichment system for the large-scale production or high-throughput isolation of EVs from liquid samples, such as culture media, plant juices, and body fluids. However, current EV enrichment methods, such as ultrafiltration and ultracentrifugation, have limited applicability owing to their associated costs, inefficiency, scalability, and centrifugation time.

Visual interpretation of deep learning model in ECG classification: A comprehensive evaluation of feature attribution methods.

Feature attribution methods can visually highlight specific input regions containing influential aspects affecting a deep learning model's prediction. Recently, the use of feature attribution methods in electrocardiogram (ECG) classification has been sharply increasing, as they assist clinicians in understanding the model's decision-making process and assessing the model's reliability. However, a careful study to identify suitable methods for ECG datasets has been lacking, leading researchers to select methods without a thorough understanding of their appropriateness.

Towards a rigorous analysis of mutual information in contrastive learning.

Contrastive learning has emerged as a cornerstone in unsupervised representation learning. Its primary paradigm involves an instance discrimination task utilizing InfoNCE loss where the loss has been proven to be a form of mutual information. Consequently, it has become a common practice to analyze contrastive learning using mutual information as a measure.

A multimodal virtual vision platform as a next-generation vision system for a surgical robot.

Robot-assisted surgery platforms are utilized globally thanks to their stereoscopic vision systems and enhanced functional assistance. However, the necessity of ergonomic improvement for their use by surgeons has been increased. In surgical robots, issues with chronic fatigue exist owing to the fixed posture of the conventional stereo viewer (SV) vision system.

Perilla-Leaf-Derived Extracellular Vesicles Selectively Inhibit Breast Cancer Cell Proliferation and Invasion.

Breast cancer is a common type of cancer characterized by high mortality rates. However, chemotherapy is not selective and often leads to side-effects. Therefore, there is a need for the development of highly efficient drugs.

In Situ Simultaneous Detection of Surface Protein and microRNA in Clustered Extracellular Vesicles from Cancer Cell Lines Using Flow Cytometry.

Extracellular vesicles (EVs) are becoming increasingly important in liquid biopsy for cancer because they contain multiple biomarkers, including proteins and RNAs, and circulate throughout the body. Cancer cell-derived EVs are highly heterogeneous, and multiplexed biomarker detection techniques are required to improve the accuracy of diagnosis. In addition, in situ EV biomarker detection increases the efficiency of the detection process because EVs are difficult to handle.

Brain endothelial cell-derived extracellular vesicles with a mitochondria-targeting photosensitizer effectively treat glioblastoma by hijacking the blood‒brain barrier.

Glioblastoma (GBM) is the most aggressive malignant brain tumor and has a high mortality rate. Photodynamic therapy (PDT) has emerged as a promising approach for the treatment of malignant brain tumors. However, the use of PDT for the treatment of GBM has been limited by its low blood‒brain barrier (BBB) permeability and lack of cancer-targeting ability.

Machine Learning Prediction for the Recurrence After Electrical Cardioversion of Patients With Persistent Atrial Fibrillation.

Background And Objectives: There is limited evidence regarding machine-learning prediction for the recurrence of atrial fibrillation (AF) after electrical cardioversion (ECV). This study aimed to predict the recurrence of AF after ECV using machine learning of clinical features and electrocardiograms (ECGs) in persistent AF patients.

Methods: We analyzed patients who underwent successful ECV for persistent AF.

Bioreducible exosomes encapsulating glycolysis inhibitors potentiate mitochondria-targeted sonodynamic cancer therapy via cancer-targeted drug release and cellular energy depletion.

Nanocarrier-assisted sonodynamic therapy (SDT) has shown great potential for the effective and targeted treatment of deep-seated tumors by overcoming the critical limitations of sonosensitizers. However, in vivo SDT using nanocarriers is still constrained by their intrinsic toxicity and nonspecific cargo release. In this study, we developed bioreducible exosomes for the safe and tumor-specific delivery of mitochondria-targeting sonosensitizers [triphenylphosphonium-conjugated chlorin e6 (T-Ce6)] and glycolysis inhibitors (FX11).

An effective low-rank compression with a joint rank selection followed by a compression-friendly training.

Low-rank compression of a neural network is one of the popular compression techniques, where it has been known to have two main challenges. The first challenge is determining the optimal rank of all the layers and the second is training the neural network into a compression-friendly form. To overcome the two challenges, we propose BSR (Beam-search and Stable Rank), a low-rank compression algorithm that embodies an efficient rank-selection method and a unique compression-friendly training method.

Mitochondria-targeting sonosensitizer-loaded extracellular vesicles for chemo-sonodynamic therapy.

Sonodynamic therapy (SDT) has emerged as an effective therapeutic modality as it employs ultrasound (US) to eradicate deep-seated tumors noninvasively. However, the therapeutic efficacy of SDT in clinical settings remains limited owing to the low aqueous stability and poor pharmacokinetic properties of sonosensitizers. In this study, extracellular vesicles (EVs), which have low systemic toxicity, were used as clinically available nanocarriers to effectively transfer a sonosensitizer to cancer cells.

Genomic and physiological analysis of C carotenoid-producing novel Halorubrum ruber sp. nov.

A novel haloarchaeal species designated as MBLA0099 was isolated from seawater near Yeongheung Island. Cells were Gram-negative, non-motile, red-pigmented, and rod-shaped. They grew at 10-45°C, within pH 5.

Size-selective filtration of extracellular vesicles with a movable-layer device.

This paper presents a microfluidic device that can isolate extracellular vesicles (EVs) with multiple size intervals in a simple, effective, and automated manner. We accomplish this size-selective separation using a vertically movable plunger and a rotationally movable chip. The chip has open chambers with nanoporous filters that are sequentially connected by check valves.

Isolation and Characterization of Urinary Extracellular Vesicles from Healthy Donors and Patients with Castration-Resistant Prostate Cancer.

Prostate cancer (PCa) is the most commonly diagnosed malignancy among men in developed countries. The five-year survival rate for men diagnosed with early-stage PCa is approximately 100%, while it is less than 30% for castration-resistant PCa (CRPC). Currently, the detection of prostate-specific antigens as biomarkers for the prognosis of CRPC is criticized because of its low accuracy, high invasiveness, and high false-positive rate.

Extracellular vesicles with high dual drug loading for safe and efficient combination chemo-phototherapy.

Extracellular vesicles (EVs) have emerged as biocompatible nanocarriers for efficient delivery of various therapeutic agents, with intrinsic long-term blood circulatory capability and low immunogenicity. Here, indocyanine green (ICG)- and paclitaxel (PTX)-loaded EVs [EV(ICG/PTX)] were developed as a biocompatible nanoplatform for safe and efficient cancer treatment through near-infrared (NIR) light-triggered combination chemo/photothermal/photodynamic therapy. High dual drug encapsulation in EVs was achieved for both the hydrophilic ICG and hydrophobic PTX by simple incubation.

Engineered extracellular vesicle-based sonotheranostics for dual stimuli-sensitive drug release and photoacoustic imaging-guided chemo-sonodynamic cancer therapy.

Sonodynamic therapy has shown promise as an effective alternative to conventional photodynamic therapy owing to its ability to treat deep-seated tumors. However, the development of stimuli-responsive sonosensitizers with high biocompatibility faces a significant challenge. In this study, we developed dual stimuli-responsive sonosensitizers with desirable biosafety using extracellular vesicles (EVs), a class of naturally occurring nanoparticles.

Inhibition of tumor progression and M2 microglial polarization by extracellular vesicle-mediated microRNA-124 in a 3D microfluidic glioblastoma microenvironment.

Glioblastoma (GBM) is one of the most aggressive types of brain cancer. GBM progression is closely associated with microglia activation; therefore, understanding the regulation of the crosstalk between human GBM and microglia may help develop effective therapeutic strategies. Elucidation of efficient delivery of microRNA (miRNA) via extracellular vesicles (EVs) and their intracellular communications is required for therapeutic applications in GBM treatment.

Antioxidative Effects of Carrot-Derived Nanovesicles in Cardiomyoblast and Neuroblastoma Cells.

Oxidative stress is implicated in many diseases, including cardiovascular and neurodegenerative diseases. Because an increased level of oxidative stress causes apoptosis, it is necessary to inhibit cellular responses to oxidative stress. In this study, Carex, a nanovesicle from carrot, was isolated and investigated as a novel biomaterial with antioxidative function in cardiomyoblasts and neuroblastoma cells.