Polymeric pH-Responsive Metal-Supramolecular Nanoparticles for Synergistic Chemo-Photothermal Therapy.

Stimuli-responsive drug delivery carriers, particularly those exhibiting pH sensitivity, have attracted significant scholarly interest due to their promising potential in anticancer therapeutic applications. This phenomenon can primarily be ascribed to the inherently acidic nature of tumor microenvironments. However, pH-responsive carriers frequently require the incorporation of functional groups or materials sensitive to pH changes. Given the pH-sensitive characteristics of metal coordination with natural small-molecule drugs, organometallic supramolecules present a facile and effective strategy for integrating pH-responsive behavior into these systems. Meanwhile, utilizing the natural compound luteolin in conjunction with iron ions (Fe3+) through the advanced engineering technique of flash nanoprecipitation (FNP) results in the synthesis of stable, highly loaded nanoparticles (NPs) exhibiting a supramolecular photothermal effect. Our experimental findings substantiate that the photothermal effect persists over time, even after the pH-responsive release phase has ended. Consequently, these polymeric pH-responsive metallic supramolecular nanoparticles integrate chemotherapy and photothermal therapy, creating a synergistic approach to cancer treatment. This bifunctional platform, which exhibits both pH-responsive and photothermal properties, presents a highly promising avenue for biomedical applications, particularly in the area of tumor therapies. Its dual function offers a potentially efficacious approach to tumor treatment.

Enhancing Prediction of Myocardial Recovery After Coronary Revascularization: Integrating Radiomics from Myocardial Contrast Echocardiography with Machine Learning.

Introduction: Chronic coronary artery disease (CAD) management often relies on myocardial contrast echocardiography (MCE), yet its effectiveness is limited by subjective interpretations and difficulty in distinguishing hibernating from necrotic myocardium. This study explores the integration of machine learning (ML) with radiomics to predict functional recovery in dyskinetic myocardial segments in CAD patients undergoing revascularization, aiming to overcome these limitations. Methods: This prospective study enrolled 55 chronic CAD patients, dividing into training (39 patients, 205 segments) and testing sets (16 patients, 68 segments). Dysfunctional myocardial segments were identified by initial wall motion scores (WMS) of ≥2 (hypokinesis or higher). Functional recovery was defined as a decrease of ≥1 grade in WMS during follow-up echocardiography. Radiomics features were extracted from dyssynergic segments in end-systolic phase MCE images across five cardiac cycles post- "flash" impulse and processed through a five-step feature selection. Four ML classifiers were trained and compared using these features and MCE parameters, to identify the optimal model for myocardial recovery prediction. Results: Functional improvement was noted in 139 out of 273 dyskinetic segments (50.9%) following revascularization. Receiver Operating Characteristic (ROC) analysis determined that myocardial blood flow (MBF) was the most precise clinical predictor of recovery, with an area under the curve (AUC) of 0.770. Approximately 1.34 million radiomics features were extracted, with nine features identified as key predictors of myocardial recovery. The random forest (RF) model, integrating MBF values and radiomics features, demonstrated superior predictive accuracy over other ML classifiers. Validation of the RF model on the testing dataset demonstrated its effectiveness, evidenced by an AUC of 0.821, along with consistent calibration and clinical utility. Conclusion: The integration of ML with radiomics from MCE effectively predicts myocardial recovery in CAD. The RF model, combining radiomics and MBF values, presents a non-invasive, precise approach, significantly enhancing CAD management.

Modeling of a second harmonic spectrum in passive phase demodulation.

Spectral compression by passive phase demodulation provides an effective way to obtain a high-power single-frequency second harmonic (SH) laser. In this method, a single-frequency laser is broadened by (0, π) binary phase modulation for stimulated Brillouin scattering suppression in a high-power fiber amplifier and compressed to single frequency after frequency doubling. The effectiveness of compressing is determined by the properties of the phase modulation system, including the modulation depth, frequency response of modulation system, and modulation signal noise. A numerical model is developed to simulate the influence of these factors on the SH spectrum. The simulation results reproduce the experimental observation well, including the reduction of the compression rate at higher-frequency phase modulation, emergence of spectral sidebands and pedestal.

Nomogram for predicting skip metastasis in cN0 papillary thyroid cancer patients at increased risk of lymph node metastasis.

BACKGROUND: Skip lymph node metastasis (SLNM) refers to lateral lymph node metastasis (LLNM) without involving central lymph node (CLN). Some microscopic nodal positivity may be difficult to detect before surgery due to atypical imaging characteristics. These patients are misdiagnosed as having clinically node-negative (cN0) papillary thyroid cancer (PTC) even after central lymph node dissection, leading to a high risk of developing LNM after surgery. Current prediction models have limited clinical utility, as they are only applicable to predict SLNM from clinically node-positive (cN+) PTC, not cN0 PTC, and this has little impact on treatment strategies. OBJECTIVES: This study aimed to establish a nomogram for preoperatively assessing the likelihood of SLNM in cN0 PTC patients with increased risk of LNM, thus optimizing their therapeutic options. MATERIAL AND METHODS: The records of 780 PTC patients undergoing thyroidectomy along with bilateral central lymph node dissection were retrospectively reviewed. The cN0 patients with postoperative LLNM (occult SLNM) and cN+ patients without central lymph node metastasis (CLNM) (typical SLNM) were included in the SLNM group (n = 82). The CLNM-negative cN0 patients without postoperative LLNM were assigned to the non-SLNM group (n = 698). The independent correlates of SLNM constituted the nomogram for determining the likelihood of SLNM in high-risk cN0 PTC patients. RESULTS: The independent correlates of SLNM were age (hazard ratio (HR) = 1.016), tumor location (HR = 1.801), tumor size (HR = 1.528), and capsular invasion (HR = 2.941). They served as components in the development of the nomogram. This model was verified to present acceptable discrimination. It showed good calibration and a decent net benefit when the predicted probability was <60%. CONCLUSIONS: We developed a nomogram incorporating preoperative clinical data to predict the probability of SLNM development in high-risk cN0 PTC patients, which contributed to their optimized treatment options.

The Pandora Effect: The Power and Peril of Curiosity.

Curiosity-the desire for information-underlies many human activities, from reading celebrity gossip to developing nuclear science. Curiosity is well recognized as a human blessing. Is it also a human curse? Tales about such things as Pandora's box suggest that it is, but scientific evidence is lacking. In four controlled experiments, we demonstrated that curiosity could lead humans to expose themselves to aversive stimuli (even electric shocks) for no apparent benefits. The research suggests that humans possess an inherent desire, independent of consequentialist considerations, to resolve uncertainty; when facing something uncertain and feeling curious, they will act to resolve the uncertainty even if they expect negative consequences. This research reveals the potential perverse side of curiosity, and is particularly relevant to the current epoch, the epoch of information, and to the scientific community, a community with high curiosity.

Approach aversion: negative hedonic reactions toward approaching stimuli.

We live in a dynamic world, surrounded by moving stimuli-moving people, moving objects, and moving events. The current research proposes and finds an approach aversion effect-individuals feel less positively (or more negatively) about a stimulus if they perceive it to be approaching rather than receding or static. The effect appears general, occurring whether the stimulus is initially negative or nonnegative and whether it moves in space (toward or away from "here"), in time (toward or away from "now"), or in probability (toward or away from "sure"). This research complements extensive existing research on perceived static distance of stimuli (near vs. far) by exploring perceived dynamic movement of stimuli (approaching vs. receding), showing that the effect of movement is distinct from the effect of distance.