Mechanical stimuli-driven cancer therapeutics.

Mechanical stimulation utilizing deep tissue-penetrating and focusable energy sources, such as ultrasound and magnetic fields, is regarded as an emerging patient-friendly and effective therapeutic strategy to overcome the limitations of conventional cancer therapies based on fundamental external stimuli such as light, heat, electricity, radiation, or microwaves. Recent efforts have suggested that mechanical stimuli-driven cancer therapy (henceforth referred to as "mechanical cancer therapy") could provide a direct therapeutic effect and intelligent control to augment other anti-cancer systems as a synergistic combinational cancer treatment. This review article highlights the latest advances in mechanical cancer therapy to present a novel perspective on the fundamental principles of ultrasound- and magnetic field-mediated mechanical forces, including compression, tension, shear force, and torque, that can be generated in a cellular microenvironment using mechanical stimuli-activated functional materials. Additionally, this article will shed light on mechanical cancer therapy and inspire future research to pursue the development of ultrasound- and magnetic-field-activated materials and their applications in this field.

One-dimensional nanomaterials for cancer therapy and diagnosis.

One-dimensional (1-D) nanomaterials possess unique shape-dependent phyicochemical properties and are increasingly recognized as promising materials for nanotechnology. 1-D nanomaterials can be classified according to their shape, such as nanorods, nanotubes, nanowires, self-assembled nanochains, etc., and have been applied in electronics, photonics, and catalysis. The biological characteristics of 1-D nanomaterials, including high drug loading efficiency, prolonged blood circulation, the ability to capture cancer cells, unique cellular uptake mechanisms, efficient photothermal conversion, and material tunability, have aided in extending their potential to biomedical applications, particularly in cancer therapy and diagnosis. This review highlights a novel perspective on emerging 1-D nanomaterials for cancer therapy and diagnosis by introducing the definition of 1-D nanomaterials, their shape-dependent physicochemical properties, biomedical applications, and recent advances in cancer therapy and diagnosis. This review also proposes unexplored potential nanomaterial types and therapeutic applications for 1-D nanomaterials. In particular, the most significant and exciting advances in recent years, including ultrasound-enabled sonodynamic therapy, magnetic field-based therapy, and bioresponsive 1-D nanomaterials for intracellular self-assembly in situ, are discussed along with novel therapeutic concepts, such as piezoelectric 1-D nanomaterials, nanozyme-based nanomedicine, and others.

Stimuli-responsive ferroptosis for cancer therapy.

Ferroptosis, an iron-dependent programmed cell death mechanism, is regulated by distinct molecular pathways of lipid peroxidation caused by intracellular iron supplementation and glutathione (GSH) synthesis inhibition. It has attracted a great deal of attention as a viable alternative to typical apoptosis-based cancer therapy that exhibits drug resistance. For efficient therapeutic utilization of such a unique and desirable mechanism, precise control using various stimuli to activate the administered nanocarriers is essential. Specific conditions in the tumor microenvironment (e.g., acidic pH, high level of ROS and GSH, hypoxia, etc.) can be exploited as endogenous stimuli to ensure high specificity of the tumor site. Maximized spatiotemporal controllability can be assured by utilizing external energy sources (e.g., magnetic fields, ultrasound, microwaves, light, etc.) as exogenous stimuli that can provide on-demand remote controllability for customized deep tumor therapy with a low inter-patient variation. Strikingly, the utilization of dual endogenous and/or exogenous stimuli provides a new direction for efficient cancer therapy. This review highlights recent advances in the utilization of various endogenous and exogenous stimuli to activate the reactions of nanocarriers for ferroptosis-based cancer therapy that can inspire the field of cancer therapy, particularly for the treatment of intractable tumors.

Magnetic Control and Real-Time Monitoring of Stem Cell Differentiation by the Ligand Nanoassembly.

Native extracellular matrix (ECM) exhibits dynamic change in the ligand position. Herein, the ECM-emulating control and real-time monitoring of stem cell differentiation are demonstrated by ligand nanoassembly. The density of gold nanoassembly presenting cell-adhesive Arg-Gly-Asp (RGD) ligand on Fe3 O4 (magnetite) nanoparticle in nanostructures flexibly grafted to material is changed while keeping macroscale ligand density invariant. The ligand nanoassembly on the Fe3 O4 can be magnetically attracted to mediate rising and falling ligand movements via linker stretching and compression, respectively. High ligand nanoassembly density stimulates integrin ligation to activate the mechanosensing-assisted stem cell differentiation, which is monitored via in situ real-time electrochemical sensing. Magnetic control of rising and falling ligand movements hinders and promotes the adhesion-mediated mechanotransduction and differentiation of stem cells, respectively. These rising and falling ligand states yield the difference in the farthest distance (≈34.6 nm) of the RGD from material surface, thereby dynamically mimicking static long and short flexible linkers, which hinder and promote cell adhesion, respectively. Design of cytocompatible ligand nanoassemblies can be made with combinations of dimensions, shapes, and biomimetic ligands for remotely regulating stem cells for offering novel methodologies to advance regenerative therapies.

Photonic control of ligand nanospacing in self-assembly regulates stem cell fate.

Extracellular matrix (ECM) undergoes dynamic inflation that dynamically changes ligand nanospacing but has not been explored. Here we utilize ECM-mimicking photocontrolled supramolecular ligand-tunable Azo+ self-assembly composed of azobenzene derivatives (Azo+) stacked via cation-π interactions and stabilized with RGD ligand-bearing poly(acrylic acid). Near-infrared-upconverted-ultraviolet light induces cis-Azo+-mediated inflation that suppresses cation-π interactions, thereby inflating liganded self-assembly. This inflation increases nanospacing of "closely nanospaced" ligands from 1.8 nm to 2.6 nm and the surface area of liganded self-assembly that facilitate stem cell adhesion, mechanosensing, and differentiation both in vitro and in vivo, including the release of loaded molecules by destabilizing water bridges and hydrogen bonds between the Azo+ molecules and loaded molecules. Conversely, visible light induces trans-Azo+ formation that facilitates cation-π interactions, thereby deflating self-assembly with "closely nanospaced" ligands that inhibits stem cell adhesion, mechanosensing, and differentiation. In stark contrast, when ligand nanospacing increases from 8.7 nm to 12.2 nm via the inflation of self-assembly, the surface area of "distantly nanospaced" ligands increases, thereby suppressing stem cell adhesion, mechanosensing, and differentiation. Long-term in vivo stability of self-assembly via real-time tracking and upconversion are verified. This tuning of ligand nanospacing can unravel dynamic ligand-cell interactions for stem cell-regulated tissue regeneration.

Analysis of Effect of Intensity of Aerobic Exercise on Cognitive and Motor Functions and Neurotrophic Factor Expression Patterns in an Alzheimer's Disease Rat Model.

The effect of aerobic exercise at different intensities on Alzheimer's disease (AD) still remains unclear. We investigated the effect of aerobic exercise at different intensities on cognitive and motor functions and neurotrophic factor expression. Thirty-two AD-induced rats were randomly assigned to control (CG), low-intensity (Group I), medium-intensity (Group II), and high-intensity (Group III) exercise groups. Each group, except for the CG, performed aerobic exercise for 20 min a day five times a week. After performing aerobic exercise for 4 weeks, their cognitive and motor functions and neurotrophic factor expression patterns were analyzed and compared between the groups. All variables of cognitive and motor functions and neurotrophic factor expression were significantly improved in Groups I, II, and III compared to those in the CG (p < 0.05). Among the neurotrophic factors, brain-derived neurotrophic factor (BDNF) expression was significantly improved in Group III compared to that in Groups I and II (p < 0.05). In the intra-group comparison of cognitive and motor functions, no significant difference was observed in CG, but the aerobic exercise groups showed improvements. Only Group III showed a significant improvement in the time it took to find eight food items accurately (p < 0.05). Aerobic exercise improved the cognitive and motor functions and neurotrophic factor expression patterns in the AD-induced rat model, with high-intensity aerobic exercise having greater effects on cognitive function and BDNF expression.

An augmented reality mobile application for weight estimation in paediatric patients: A prospective single-blinded cross-sectional study.

Introduction: Determining the exact weight of children is a challenging task during emergency situations. Current guidelines recommend the use of length-based weight-estimating tapes. However, healthcare providers must either always carry the tapes or take time to locate them. Moreover, they may not know how to use them. To address these issues, we developed an augmented reality smartphone application for length-based weight estimation called the Paediatric Augmented Reality Scale (PARS). We evaluated its performance and compared it to that of the Broselow tape (BT) and Paediatric Advanced Weight Prediction in the Emergency Room extra-long and extra-large (PAWPER-XL) tape methods. Method: A prospective, single-blinded cross-sectional study was conducted with children aged 1 month to 12 years who visited the emergency department of the tertiary university hospital in Bucheon, South Korea between July 2021 and February 2022. This study aimed to evaluate the measurement agreement and performance of 3 methods: BT, PAWPER-XL and PARS. Results: In all, 1090 participants were enrolled, and 639 (58.6%) were male. The mean age of the participants was 4.1 ± 2.8 years, with a mean height of 102.7 ± 21.7 cm and mean weight of 18.8 ± 9.5 kg. Compared to BT and PAWPER-XL, PARS exhibited lower mean absolute percentage error (9.60%) and root mean square percentage error (3.02%). PARS achieved a higher proportion of weights estimated within 10% of the actual weight (63.21%), outperform-ing BT (57.25%) and PAWPER-XL (62.47%). The intraclass correlation coefficients for the actual and estimated weights of BT, PAWPER-XL and PARS were 0.952, 0.969 and 0.973, respectively (P<0.001). Conclusion: PARS exhibited a modestly better performance than BT and PAWPER-XL in estimating body weight. PARS-estimated body weights correlated fairly accurately with the actual body weights. PARS holds potential utility in paediatric emergencies.

Hierarchical Structured Component Analysis for Microbiome Data Using Taxonomy Assignments.

The recent advent of high-throughput sequencing technology has enabled us to study the associations between human microbiome and diseases. The DNA sequences of microbiome samples are clustered as operational taxonomic units (OTUs) according to their similarity. The OTU table containing counts of OTUs present in each sample is used to measure correlations between OTUs and disease status and find key microbes for prediction of the disease status. Various statistical methods have been proposed for such microbiome data analysis. However, none of these methods reflects the hierarchy of taxonomy information. In this paper, we propose a hierarchical structural component model for microbiome data (HisCoM-microb) using taxonomy information as well as OTU table data. The proposed HisCoM-microb consists of two layers: one for OTUs and the other for taxa at the higher taxonomy level. Then we calculate simultaneously coefficient estimates of OTUs and taxa of the two layers inserted in the hierarchical model. Through this analysis, we can infer the association between taxa or OTUs and disease status, considering the impact of taxonomic structure on disease status. Both simulation study and real microbiome data analysis show that HisCoM-microb can successfully reveal the relations between each taxon and disease status and identify the key OTUs of the disease at the same time.

The Effect of Lumbar Belts with Different Extensibilities on Kinematic, Kinetic, and Muscle Activity of Sit-to-Stand Motions in Patients with Nonspecific Low Back Pain.

Although lumbar belts can be used for the treatment and prevention of low back pain, the role of the lumbar belt remains unclear without clear guidelines. This study aimed to investigate the effect of lumbar belts with different extensibilities on the kinematics, kinetics, and muscle activity of sit-to-stand motions in terms of motor control in patients with nonspecific low back pain. A total of 30 subjects participated in the study: 15 patients with nonspecific low back pain and 15 healthy adults. Participants performed the sit-to-stand motion in random order of three conditions: no lumbar belt, wearing an extensible lumbar belt, and wearing a non-extensible lumbar belt. The sit-to-stand motion's kinematic, kinetic, and muscle activity variables in each condition were measured using a three-dimensional motion analysis device, force plate, and surface electromyography. An interaction effect was found for the time taken, anterior pelvic tilt angle, and muscle activity of the vastus lateralis and biceps femoris. The two lumbar belts with different extensibilities had a positive effect on motor control in patients with nonspecific low back pain. Therefore, both types of extensible lumbar belts can be useful in the sit-to-stand motion, which is an important functional activity for patients with nonspecific low back pain.

Predicting preterm birth through vaginal microbiota, cervical length, and WBC using a machine learning model.

An association between the vaginal microbiome and preterm birth has been reported. However, in practice, it is difficult to predict premature birth using the microbiome because the vaginal microbial community varies highly among samples depending on the individual, and the prediction rate is very low. The purpose of this study was to select markers that improve predictive power through machine learning among various vaginal microbiota and develop a prediction algorithm with better predictive power that combines clinical information. As a multicenter case-control study with 150 Korean pregnant women with 54 preterm delivery group and 96 full-term delivery group, cervicovaginal fluid was collected from pregnant women during mid-pregnancy. Their demographic profiles (age, BMI, education level, and PTB history), white blood cell count, and cervical length were recorded, and the microbiome profiles of the cervicovaginal fluid were analyzed. The subjects were randomly divided into a training (n = 101) and a test set (n = 49) in a two-to-one ratio. When training ML models using selected markers, five-fold cross-validation was performed on the training set. A univariate analysis was performed to select markers using seven statistical tests, including the Wilcoxon rank-sum test. Using the selected markers, including Lactobacillus spp., Gardnerella vaginalis, Ureaplasma parvum, Atopobium vaginae, Prevotella timonensis, and Peptoniphilus grossensis, machine learning models (logistic regression, random forest, extreme gradient boosting, support vector machine, and GUIDE) were used to build prediction models. The test area under the curve of the logistic regression model was 0.72 when it was trained with the 17 selected markers. When analyzed by combining white blood cell count and cervical length with the seven vaginal microbiome markers, the random forest model showed the highest test area under the curve of 0.84. The GUIDE, the single tree model, provided a more reasonable biological interpretation, using the 10 selected markers (A. vaginae, G. vaginalis, Lactobacillus crispatus, Lactobacillus fornicalis, Lactobacillus gasseri, Lactobacillus iners, Lactobacillus jensenii, Peptoniphilus grossensis, P. timonensis, and U. parvum), and the covariates produced a tree with a test area under the curve of 0.77. It was confirmed that the association with preterm birth increased when P. timonensis and U. parvum increased (AUC = 0.77), which could also be explained by the fact that as the number of Peptoniphilus lacrimalis increased, the association with preterm birth was high (AUC = 0.77). Our study demonstrates that several candidate bacteria could be used as potential predictors for preterm birth, and that the predictive rate can be increased through a machine learning model employing a combination of cervical length and white blood cell count information.

Dynamic Ligand Screening by Magnetic Nanoassembly Modulates Stem Cell Differentiation.

In native microenvironment, diverse physical barriers exist to dynamically modulate stem cell recruitment and differentiation for tissue repair. In this study, nanoassembly-based magnetic screens of various sizes are utilized, and they are elastically tethered over an RGD ligand (cell-adhesive motif)-presenting material surface to generate various nanogaps between the screens and the RGDs without modulating the RGD density. Large screens exhibiting low RGD distribution stimulate integrin clustering to facilitate focal adhesion, mechanotransduction, and differentiation of stem cells, which are not observed with small screens. Magnetic downward pulling of the large screens decreases the nanogaps, which dynamically suppress the focal adhesion, mechanotransduction, and differentiation of stem cells. Conversely, magnetic upward pulling of the small screens increases the nanogaps, which dynamically activates focal adhesion, mechanotransduction, and differentiation of stem cells. This regulation mechanism is also shown to be effective in the microenvironment in vivo. Further diversifying the geometries of the physical screens can further enable diverse modalities of multifaceted and safe unscreening of the distributed RGDs to unravel and modulate stem cell differentiation for tissue repair.

Submolecular Ligand Size and Spacing for Cell Adhesion.

Cell adhesion occurs when integrin recognizes and binds to Arg-Gly-Asp (RGD) ligands present in fibronectin. In this work, submolecular ligand size and spacing are tuned via template-mediated in situ growth of nanoparticles for dynamic macrophage modulation. To tune liganded gold nanoparticle (GNP) size and spacing from 3 to 20 nm, in situ localized assemblies of GNP arrays on nanomagnetite templates are engineered. 3 nm-spaced ligands stimulate the binding of integrin, which mediates macrophage-adhesion-assisted pro-regenerative polarization as compared to 20 nm-spaced ligands, which can be dynamically anchored to the substrate for stabilizing integrin binding and facilitating dynamic macrophage adhesion. Increasing the ligand size from 7 to 20 nm only slightly promotes macrophage adhesion, not observed with 13 nm-sized ligands. Increasing the ligand spacing from 3 to 17 nm significantly hinders macrophage adhesion that induces inflammatory polarization. Submolecular tuning of ligand spacing can dominantly modulate host macrophages.

Photoswitchable Microgels for Dynamic Macrophage Modulation.

Dynamic manipulation of supramolecular self-assembled structures is achieved irreversibly or under non-physiological conditions, thereby limiting their biomedical, environmental, and catalysis applicability. In this study, microgels composed of azobenzene derivatives stacked via π-cation and π-π interactions are developed that are electrostatically stabilized with Arg-Gly-Asp (RGD)-bearing anionic polymers. Lateral swelling of RGD-bearing microgels occurs via cis-azobenzene formation mediated by near-infrared-light-upconverted ultraviolet light, which disrupts intermolecular interactions on the visible-light-absorbing upconversion-nanoparticle-coated materials. Real-time imaging and molecular dynamics simulations demonstrate the deswelling of RGD-bearing microgels via visible-light-mediated trans-azobenzene formation. Near-infrared light can induce in situ swelling of RGD-bearing microgels to increase RGD availability and trigger release of loaded interleukin-4, which facilitates the adhesion structure assembly linked with pro-regenerative polarization of host macrophages. In contrast, visible light can induce deswelling of RGD-bearing microgels to decrease RGD availability that suppresses macrophage adhesion that yields pro-inflammatory polarization. These microgels exhibit high stability and non-toxicity. Versatile use of ligands and protein delivery can offer cytocompatible and photoswitchable manipulability of diverse host cells.

Effects of a combination of scapular stabilization and thoracic extension exercises for office workers with forward head posture on the craniovertebral angle, respiration, pain, and disability: A randomized-controlled trial.

OBJECTIVES: This study aims to investigate how exercise programs not directly applied to the cervical spine affect office workers with forward head posture (FHP). PATIENTS AND METHODS: Between March 2018 and June 2018, a total of 32 office workers with FHP (13 males, 19 females; mean age 36.63 years; range, 23 to 57 years) were randomized either to experimental (n=16) or control groups (n=16). Scapular stabilization and thoracic extension exercises were applied to the experimental group and cervical stabilization and stretching exercises to the control group. The results of the pre-intervention and after six weeks measurement of the craniovertebral angle (CVA), respiration, pain, and disability were compared and analyzed. RESULTS: For intra-group comparison, both groups showed significant differences (p<0.05) in CVA, forced expiratory volume at 1 sec (FEV1), Visual Analog Scale (VAS), and neck disability index at pre- and post-intervention, while only the experimental group showed a significant difference (p<0.05) in maximum inspiratory pressure, maximum expiratory pressure, and forced vital capacity. For inter-group comparison, a significant difference (p<0.05) between FEV1 and VAS was observed. CONCLUSION: The combination of scapular stabilization and thoracic extension exercises, not directly applied to the cervical spine, has an effect on improving the posture, respiration, neck pain, and disability in office workers with FHP.

Microbiome Markers of Pancreatic Cancer Based on Bacteria-Derived Extracellular Vesicles Acquired from Blood Samples: A Retrospective Propensity Score Matching Analysis.

Novel biomarkers for early diagnosis of pancreatic cancer (PC) are necessary to improve prognosis. We aimed to discover candidate biomarkers by identifying compositional differences of microbiome between patients with PC (n = 38) and healthy controls (n = 52), using microbial extracellular vesicles (EVs) acquired from blood samples. Composition analysis was performed using 16S rRNA gene analysis and bacteria-derived EVs. Statistically significant differences in microbial compositions were used to construct PC prediction models after propensity score matching analysis to reduce other possible biases. Between-group differences in microbial compositions were identified at the phylum and genus levels. At the phylum level, three species (Verrucomicrobia, Deferribacteres, and Bacteroidetes) were more abundant and one species (Actinobacteria) was less abundant in PC patients. At the genus level, four species (Stenotrophomonas, Sphingomonas, Propionibacterium, and Corynebacterium) were less abundant and six species (Ruminococcaceae UCG-014, Lachnospiraceae NK4A136 group, Akkermansia, Turicibacter, Ruminiclostridium, and Lachnospiraceae UCG-001) were more abundant in PC patients. Using the best combination of these microbiome markers, we constructed a PC prediction model that yielded a high area under the receiver operating characteristic curve (0.966 and 1.000, at the phylum and genus level, respectively). These microbiome markers, which altered microbial compositions, are therefore candidate biomarkers for early diagnosis of PC.

Metagenomic Analysis of Serum Microbe-Derived Extracellular Vesicles and Diagnostic Models to Differentiate Ovarian Cancer and Benign Ovarian Tumor.

We aimed to develop a diagnostic model identifying ovarian cancer (OC) from benign ovarian tumors using metagenomic data from serum microbe-derived extracellular vesicles (EVs). We obtained serum samples from 166 patients with pathologically confirmed OC and 76 patients with benign ovarian tumors. For model construction and validation, samples were randomly divided into training and test sets in the ratio 2:1. Isolation of microbial EVs from serum samples of the patients and 16S rDNA amplicon sequencing were carried out. Metagenomic and clinicopathologic data-based OC diagnostic models were constructed in the training set and then validated in the test set. There were significant differences in the metagenomic profiles between the OC and benign ovarian tumor groups; specifically, genus Acinetobacter was significantly more abundant in the OC group. More importantly, Acinetobacter was the only common genus identified by seven different statistical analysis methods. Among the various metagenomic and clinicopathologic data-based OC diagnostic models, the model consisting of age, serum CA-125 levels, and relative abundance of Acinetobacter showed the best diagnostic performance with the area under the receiver operating characteristic curve of 0.898 and 0.846 in the training and test sets, respectively. Thus, our findings establish a metagenomic analysis of serum microbe-derived EVs as a potential tool for the diagnosis of OC.