Chain-like One-Dimensional Assembly of Mesoporous Silica Nanoparticles: An Approach To Improve Hydrogel Adhesion.

Mesoporous silica nanoparticles (MSNPs) are well known for their adhesive properties with hydrogels and living tissues. However, achieving direct contact between the silica nanoparticle surface and the adherend necessitates the removal of capping agents, which can lead to severe aggregation when exposed to wet surfaces. This aggregation is ineffective for simultaneously bridging the two adherends, resulting in a reduced adhesive strength. In this study, we designed and synthesized mesoporous silica nanochains (MSNCs) to enhance the interactions with hydrogels by promoting the formation of coarser structures with increased nanopore exposure. Chain-like one-dimensional assemblies in the MSNCs were generated by depleting the capping ligand, cetyltrimethylammonium bromide, from the surface of the MSNPs. To quantify the porous areas of the MSNCs, we analyzed scanning electron microscopy (SEM) images using an in-house SEM image analysis algorithm. Additionally, we conducted a comparative assessment of the adhesion energies of MSNCs and MSNPs on a poly(dimethylacrylamide) hydrogel using a universal testing machine. The MSNCs exhibited a maximum adhesion energy of 13.7 ± 0.7 J/m2 at 3 wt %, surpassing that of MSNPs (10.9 ± 0.3 J/m2) at 2 wt %. Moreover, the unique stacking structure of the MSNCs enabled them to maintain an adhesion energy of 13.4 ± 1.0 J/m2 at a high concentration of 9 wt %, whereas the adhesion energy of MSNPs decreased to 8.2 ± 0.4 J/m2. This underscores their potential as superior hydrogel adhesives in challenging wet tissue-like environments.

The effect of the size of gold nanoparticle contrast agents on CT imaging of the gastrointestinal tract and inflammatory bowel disease.

Ulcerative colitis (UC) is a chronic inflammatory bowel disease (IBD). CT imaging with contrast agents is commonly used for visualizing the gastrointestinal (GI) tract in UC patients. CT is a common imaging modality for evaluating IBD, especially in patients with acute abdominal pain presenting to emergency departments. CT's major limitation lies in its lack of specificity for imaging UC, as the commonly used agents are not well-suited for inflamed areas. Recent studies gastrointestinal tract (GIT) in UC. Further systemic research is needed to explore novel contrast agents that can specifically image disease processes in this disease setting.

Nanozyme-Based Robotics Approach for Targeting Fungal Infection.

Fungal pathogens have been designated by the World Health Organization as microbial threats of the highest priority for global health. It remains a major challenge to improve antifungal efficacy at the site of infection while avoiding off-target effects, fungal spreading, and drug tolerance. Here, a nanozyme-based microrobotic platform is developed that directs localized catalysis to the infection site with microscale precision to achieve targeted and rapid fungal killing. Using electromagnetic field frequency modulation and fine-scale spatiotemporal control, structured iron oxide nanozyme assemblies are formed that display tunable dynamic shape transformation and catalysis activation. The catalytic activity varies depending on the motion, velocity, and shape providing controllable reactive oxygen species (ROS) generation. Unexpectedly, nanozyme assemblies bind avidly to fungal (Candida albicans) surfaces to enable concentrated accumulation and targeted ROS-mediated killing in situ. By exploiting these tunable properties and selective binding to fungi, localized antifungal activity is achieved using in vivo-like cell spheroid and animal tissue infection models. Structured nanozyme assemblies are directed to Candida-infected sites using programmable algorithms to perform precisely guided spatial targeting and on-site catalysis resulting in fungal eradication within 10 min. This nanozyme-based microrobotics approach provides a uniquely effective and targeted therapeutic modality for pathogen elimination at the infection site.

Impact of symptomatic menopausal transition on the occurrence of depression, anxiety, and sleep disorders: A real-world multi-site study.

BACKGROUND: The menopause transition is a vulnerable period that can be associated with changes in mood and cognition. The present study aimed to investigate whether a symptomatic menopausal transition increases the risks of depression, anxiety, and sleep disorders. METHODS: This population-based, retrospective cohort study analysed data from five electronic health record databases in South Korea. Women aged 45-64 years with and without symptomatic menopausal transition were matched 1:1 using propensity-score matching. Subgroup analyses were conducted according to age and use of hormone replacement therapy (HRT). A primary analysis of 5-year follow-up data was conducted, and an intention-to-treat analysis was performed to identify different risk windows over 5 or 10 years. The primary outcome was first-time diagnosis of depression, anxiety, and sleep disorder. We used Cox proportional hazard models and a meta-analysis to calculate the summary hazard ratio (HR) estimates across the databases. RESULTS: Propensity-score matching resulted in a sample of 17,098 women. Summary HRs for depression (2.10; 95% confidence interval [CI] 1.63-2.71), anxiety (1.64; 95% CI 1.01-2.66), and sleep disorders (1.47; 95% CI 1.16-1.88) were higher in the symptomatic menopausal transition group. In the subgroup analysis, the use of HRT was associated with an increased risk of depression (2.21; 95% CI 1.07-4.55) and sleep disorders (2.51; 95% CI 1.25-5.04) when compared with non-use of HRT. CONCLUSIONS: Our findings suggest that women with symptomatic menopausal transition exhibit an increased risk of developing depression, anxiety, and sleep disorders. Therefore, women experiencing a symptomatic menopausal transition should be monitored closely so that interventions can be applied early.

Machine Learning Model for Classifying the Results of Fetal Cardiotocography Conducted in High-Risk Pregnancies.

PURPOSE: Fetal well-being is usually assessed via fetal heart rate (FHR) monitoring during the antepartum period. However, the interpretation of FHR is a complex and subjective process with low reliability. This study developed a machine learning model that can classify fetal cardiotocography results as normal or abnormal. MATERIALS AND METHODS: In total, 17492 fetal cardiotocography results were obtained from Ajou University Hospital and 100 fetal cardiotocography results from Czech Technical University and University Hospital in Brno. Board-certified physicians then reviewed the fetal cardiotocography results and labeled 1456 of them as gold-standard; these results were used to train and validate the model. The remaining results were used to validate the clinical effectiveness of the model with the actual outcome. RESULTS: In a test dataset, our model achieved an area under the receiver operating characteristic curve (AUROC) of 0.89 and area under the precision-recall curve (AUPRC) of 0.73 in an internal validation dataset. An average AUROC of 0.73 and average AUPRC of 0.40 were achieved in the external validation dataset. Fetus abnormality score, as calculated from the continuous fetal cardiotocography results, was significantly associated with actual clinical outcomes [intrauterine growth restriction: odds ratio, 3.626 (p=0.031); Apgar score 1 min: odds ratio, 9.523 (p<0.001), Apgar score 5 min: odds ratio, 11.49 (p=0.001), and fetal distress: odds ratio, 23.09 (p<0.001)]. CONCLUSION: The machine learning model developed in this study showed precision in classifying FHR signals. This suggests that the model can be applied to medical devices as a screening tool for monitoring fetal status.

An artificial intelligence electrocardiogram analysis for detecting cardiomyopathy in the peripartum period.

BACKGROUND: Peripartum cardiomyopathy (PPCM) is a fatal maternal complication, with left ventricular systolic dysfunction (LVSD; Left ventricular ejection fraction 45% or less) occurring at the end of pregnancy or in the months following delivery. The scarcity of screening tools for PPCM leads to a delayed diagnosis and increases its mortality and morbidity. We aim to evaluate an electrocardiogram (ECG)-deep learning model (DLM) for detecting cardiomyopathy in the peripartum period. METHODS: For the DLM development and internal performance test for detecting LVSD, we obtained a dataset of 122,733 ECG-echocardiography pairs from 58,530 male and female patients from two community hospitals. For the DLM external validation, this study included 271 ECG-echocardiography pairs (157 unique pregnant and postpartum period women) examined in the Ajou University Medical Center (AUMC) between January 2007 and May 2020. All included cases underwent an ECG within two weeks before or after the day of transthoracic echocardiography, which was performed within a month before delivery, or within five months after delivery. Based on the diagnostic criteria of PPCM, we analyzed the area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) to evaluate the model effectiveness. RESULTS: The ECG-based DLM detected PPCM with an AUROC of 0.877. Moreover, its sensitivity, specificity, PPV, and NPV for the detection of PPCM were 0.877, 0.833, 0.809, 0.352, and 0.975, respectively. CONCLUSIONS: An ECG-based DLM non-invasively and effectively detects cardiomyopathies occurring in the peripartum period and could be an ideal screening tool for PPCM.

An Antibacterial Nanorobotic Approach for the Specific Targeting and Removal of Multiple Drug-Resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) causes diseases ranging from skin infections to lethal sepsis and has become a serious threat to human health due to multiple-drug resistance (MDR). Therefore, a resistance-free antibacterial therapy is necessary to overcome MDR MRSA infections. In this study, an antibacterial nanorobot (Ab-nanobot) is developed wherein a cell wall-binding domain (CBD)-endolysin, acting as a sensor, is covalently conjugated with an actuator consisting of an iron oxide/silica core-shell. The CBD-endolysin sensor shows an excellent specificity to detect, bind, and accumulate on the S. aureus USA300 cell surface even in a bacterial consortium, and in host cell infections. Ab-nanobot specifically captures and kills MRSA in response to medically approved radiofrequency (RF) electromagnetic stimulation (EMS) signal. When Ab-nanobot receives the RF-EMS signal on the cell surface, actuator induces cell death in MRSA with 99.999% removal within 20 min by cell-wall damage via generation of localized heat and reactive oxygen species. The in vivo efficacy of Ab-nanobot is proven using a mice subcutaneous skin infection model. Collectively, this study offers a nanomedical resistance-free strategy to overcome MDR MRSA infections by providing a highly specific nanorobot for S. aureus.

Statistical Characterization of the Morphologies of Nanoparticles through Machine Learning Based Electron Microscopy Image Analysis.

Although transmission electron microscopy (TEM) may be one of the most efficient techniques available for studying the morphological characteristics of nanoparticles, analyzing them quantitatively in a statistical manner is exceedingly difficult. Herein, we report a method for mass-throughput analysis of the morphologies of nanoparticles by applying a genetic algorithm to an image analysis technique. The proposed method enables the analysis of over 150,000 nanoparticles with a high precision of 99.75% and a low false discovery rate of 0.25%. Furthermore, we clustered nanoparticles with similar morphological shapes into several groups for diverse statistical analyses. We determined that at least 1,500 nanoparticles are necessary to represent the total population of nanoparticles at a 95% credible interval. In addition, the number of TEM measurements and the average number of nanoparticles in each TEM image should be considered to ensure a satisfactory representation of nanoparticles using TEM images. Moreover, the statistical distribution of polydisperse nanoparticles plays a key role in accurately estimating their optical properties. We expect this method to become a powerful tool and aid in expanding nanoparticle-related research into the statistical domain for use in big data analysis.

Multifunctional Heterogeneous Carbon Nanotube Nanocomposites Assembled by DNA-Binding Peptide Anchors.

Although carbon nanotubes (CNTs) are remarkable materials with many exceptional characteristics, their poor chemical functionality limits their potential applications. Herein, a strategy is proposed for functionalizing CNTs, which can be achieved with any functional group (FG) without degrading their intrinsic structure by using a deoxyribonucleic acid (DNA)-binding peptide (DBP) anchor. By employing a DBP tagged with a certain FG, such as thiol, biotin, and carboxyl acid, it is possible to introduce any FG with a controlled density on DNA-wrapped CNTs. Additionally, different types of FGs can be introduced on CNTs simultaneously, using DBPs tagged with different FGs. This method can be used to prepare CNT nanocomposites containing different types of nanoparticles (NPs), such as Au NPs, magnetic NPs, and quantum dots. The CNT nanocomposites decorated with these NPs can be used as reusable catalase-like nanocomposites with exceptional catalytic activities, owing to the synergistic effects of all the components. Additionally, the unique DBP-DNA interaction allows the on-demand detachment of the NPs attached to the CNT surface; further, it facilitates a CNT chirality-specific NP attachment and separation using the sequence-specific programmable characteristics of oligonucleotides. The proposed method provides a novel chemistry platform for constructing new functional CNTs suitable for diverse applications.

High-throughput in-focus differential interference contrast imaging of three-dimensional orientations of single gold nanorods coated with a mesoporous silica shell.

Plasmonic gold nanorods (AuNRs) have been widely applied as optical orientation probes in many biophysical studies. However, characterizing the various three-dimensional (3D) orientations of AuNRs in the same focal plane of the objective lens is a challenging task. To overcome this challenge, we fabricated single AuNRs (10 nm × 30 nm) coated with either an elliptical or spherical mesoporous silica shell (AuNRs@mSiO2). Unlike bare AuNRs and elliptical AuNRs@mSiO2, spherical AuNRs@mSiO2 contained randomly oriented AuNR cores in 3D space, which could be observed on the same focal plane within a single frame by differential interference contrast (DIC) microscopy. The spherical AuNRs@mSiO2 thus achieved high-throughput detection. The proposed approach can overcome the limitations of the current gel-matrix method, which requires vertical scanning of the embedded AuNRs to capture different focal planes.

Clinicopathologic characteristics of ovarian clear cell carcinoma in the background of endometrioma: a surveillance strategy for an early detection of malignant transformation in patients with asymptomatic endometrioma.

OBJECTIVE: This study aimed to analyze the clinical features of clear cell carcinoma in relation to endometriosis and to determine an appropriate surveillance strategy for the early detection of malignant transformation of endometrioma in asymptomatic patients. METHODS: We retrospectively reviewed the clinicopathologic data of 50 patients with ovarian clear cell carcinoma. Clinicopathologic characteristics, treatment outcomes, and the association between endometriosis and the risk of malignant transformation were analyzed. RESULTS: Ten (20%) patients had been diagnosed with endometrioma before the diagnosis of clear cell carcinoma. The median period from the diagnosis of endometrioma to clear cell carcinoma diagnosis was 50 months (range, 12-213 months). After complete staging surgery, histological confirmation of endometriosis was possible in 35 (70%) patients. Of the 50 patients, 39 (78%) had not undergone any gynecologic surveillance until the onset of symptoms, at which time many of them presented with a rapidly growing pelvic mass (median 10 cm, range 4.6-25 cm). With the exception of 2 patients, all cancer diagnoses were made when the patients were in their late thirties, and median tumor size was found to increase along with age. Asymptomatic patients (n=11) who had regular gynecologic examinations were found to have a relatively smaller tumor size, lesser extent of tumor spread, and lower recurrence rate (P=0.011, 0.283, and 0.064, respectively). The presence of endometriosis was not related to the prognosis. CONCLUSION: Considering the duration of malignant transformation and the timing of cancer diagnosis, active surveillance might be considered from the age of the mid-thirties, with at least a 1-year interval, in patients with asymptomatic endometrioma.

From a precursor to an etchant: spontaneous inversion of the role of Au(iii) chloride for one-pot synthesis of smooth and spherical gold nanoparticles.

We report the inversion of the role of Au(iii) chloride, from a gold precursor to an etchant, for the synthesis of smooth and spherical AuNPs with nanoscale size tunability in a one-pot-system. Inversion of the role of Au(iii) chloride was achieved by regulating the ratio between the reducing agent and Au(iii) chloride.

Differences in DNA Probe-Mediated Aggregation Behavior of Gold Nanomaterials Based on Their Geometric Appearance.

Nanoparticles are used extensively to detect nucleic acid biomarkers due to their analytical applicability and sensitivity. Systems employing the surface plasmon resonance of gold nanomaterials are overwhelmingly considered to be candidates. The aggregation of gold nanomaterials mediated by the hybridization of target DNA at the interface causes a change in the surface plasmon resonance inherent in gold nanomaterials. Such changes can be measured by spectroscopy or even visualized by the naked eye, enabling effective and positive detection. The optical properties of gold nanoparticles are affected by their shape. The geometric appearance of the nanoparticles also affects their colloidal stability and aggregation behavior. In this study, we examined the effect of the geometric appearance of gold nanomaterials on DNA-mediated aggregation behavior through comparative experiments. Experimental and theoretical methods were used concurrently to derive accurate results and to support the hypotheses. Coarse-grained molecular dynamics simulations were performed with a large-scale atomic/molecular massively parallel simulator to understand the aggregation of nanoparticles with the same surface area and various aspect ratios. As a result, we confirmed that the aggregation sensitivity of nanoparticles was affected by the shape of the contact point with the gold nanomaterials. This study demonstrates that the design of a detection system should be accompanied by an in-depth review of the morphology of the nanoparticle.

Systematic study of interdependent relationship on gold nanorod synthesis assisted by electron microscopy image analysis.

Here, we systematically investigated the independent, multiple, and synergic effects of three major components, namely, ascorbic acid (AA), seed, and silver ions (Ag+), on the characteristics of gold nanorods (GNRs), i.e., longitudinal localized surface plasmon resonance (LSPR) peak position, shape, size, and monodispersity. To quantitatively assess the shape and dimensions of GNRs, we used an automated transmission electron microscopy image analysis method using a MATLAB-based code developed in-house and the concept of solidity, which is the ratio between the area of a GNR and the area of its convex hull. The solidity of a straight GNR is close to 1, while it decreases for both dumbbell- and dogbone-shaped GNRs. We found that the LSPR peak position, shape, and monodispersity of the GNRs all altered simultaneously with changes in the amounts of individual components. For example, as the amount of AA increased, both the LSPR peak and solidity decreased, while the polydispersity increased. In contrast, as the amount of seeds increased, both the LSPR and solidity increased, while the monodispersity improved. More importantly, we found that the influence of each component can actually change depending on the composition of the GNR growth solution. For instance, the LSPR peak position red-shifted as the amount of AA increased when the seed content was low, whereas it blue-shifted when the seed content was high.

Size-controlled growth and antibacterial mechanism for Cu:C nanocomposite thin films.

The interdependence of 'size' and 'volume-fraction' hinders the identification of their individual role in the interface properties of metal nanoparticles (NPs) embedded in a matrix. Here, the case of Cu NPs embedded in a C matrix is presented for their profound antibacterial activity. Cu:C nanocomposite thin films with fixed Cu content (≈12 atomic%) are prepared using a plasma process where plasma energy controls the size of Cu NPs (from 9 nm to 16 nm). An inverse relationship between the size-effect on antibacterial activity against Escherichia coli and Staphylococcus aureus bacteria is established through the real time monitoring of an aliquot by inductively coupled plasma mass spectrometry, which confirmed the inverse relationship of Cu ion release from the nanocomposite with varied Cu NP sizes. It was found that enhancing the total power density increases the plasma density as well as effective kinetic energy of the plasma species, which in turn creates a large number of nucleation sites and restricts the island kind of growth of Cu NPs. The mechanism of NP size-control is illustrated on the basis of ion density and nucleation and the growth regime of plasma species. This physical approach to NP size reduction anticipates a contamination-free competitive recipe of size-control to capping based chemical methods.

Ultrastable-Stealth Large Gold Nanoparticles with DNA Directed Biological Functionality.

The stability of gold nanoparticles (AuNPs) in biological samples is very important for their biomedical applications. Although various molecules such as polystyrenesulfonate (PSS), phosphine, DNA, and polyethylene glycol (PEG) have been used to stabilize AuNPs, it is still very difficult to stabilize large AuNPs. As a result, biomedical applications of large (30-100 nm) AuNPs are limited, even though they possess more favorable optical properties and are easier to be taken up by cells than smaller AuNPs. To overcome this limitation, we herein report a novel method of preparing large (30-100 nm) AuNPs with a high colloidal stability and facile chemical or biological functionality, via surface passivation with an amphiphilic polymer polyvinylpyrrolidone (PVP). This PVP passivation results in an extraordinary colloidal stability for 13, 30, 50, 70, and 100 nm AuNPs to be stabilized in PBS for at least 3 months. More importantly, the PVP capped AuNPs (AuNP-PVP) were also resistant to protein adsorption in the presence of serum containing media and exhibit a negligible cytotoxicity. The AuNP-PVPs functionalized with a DNA aptamer AS1411 remain biologically active, resulting in significant increase in the uptake of the AuNPs (∼12,200 AuNPs per cell) in comparison with AuNPs capped by a control DNA of the same length. The novel method developed in this study to stabilize large AuNPs with high colloidal stability and biological activity will allow much wider applications of these large AuNPs for biomedical applications, such as cellular imaging, molecular diagnosis, and targeted therapy.

Dental Hetero-Graft Materials with Nano Hydroxyapatite Surface Treatment.

We report the development of hydroxyapatite nanoparticle (HAp NP)-functionalized hetero-graft materials (HGMs) for dental applications. These HGMs were prepared by attaching platelet-, needle-, and sphere-shaped HAp NPs to the surface of xenograft materials through chemical conjugation. Although all three HAp NPs contributed to increase the surface area of bone graft material (BGM), the shape of the HAp NPs was a determining factor. Platelet HAp NPs were most effective, because they caused a 48.9% increase in BGM surface area whereas the influence of the spherical NP was only a 6.7% increase. This suggests that geometric factors regarding both the attached HAp NPs and graft material surface are essential in controlling the surface roughness of graft materials. Among the three HAp NPs, it was the platelet HAp NPs that helped to increase the efficacy of the BGM most significantly. Compared with BGM with no HAp NP attachment, HGM with platelet HAp NP ('platelet-HGM) treatment had ~46.1% higher cell attachment and proliferation rate. The MTT assay also showed that the HAp NP-treated hetero-graft materials had negligible cytotoxicity.