Magnetic microrobots assist in medical tasks such as imaging, drug delivery, and painless examinations. They are wireless, battery-free, and safe for the human body.

However, current microrobots face several limitations:

• Simple Shapes: Difficult to create complex or flexible designs.

• Fixed Functions: Their movement or shape cannot be changed once fabricated.

• Manufacturing Limits: Techniques like 3D printing restrict design diversity and adaptability.

Dynamic Vision Sensors (DVS) and Vision Transformers (ViTs) lead computer vision technology with efficient object recognition and image processing. However, DVS data's high computational complexity poses a problem for its real-time implementations. Merging these technologies can enhance vision system performance in dynamic environments and optimize real-time DVS processing. The research team use a ViT architecture to classify the DVS 128 dataset and compare results with existing works using SNNs. They experiment with different DVS-to-ViT input patch sizes and conclude that the large patch size of 32x32 pixels has better accuracy and smaller loss than the 4x4 pixel patches as epochs increase. The novel method also achieved a high 98.4% accuracy and low 0.22 loss within five epochs, significantly outperforming previous works averaging 93.13% accuracy over more epochs. These results highlight ViTs' large potential for real-time DVS data classification in applications that require high accuracy, like autonomous vehicles and surveillance systems.

Accurate diagnosis of inflammation, including its location and boundary, is of immense value to subsequent therapy. As one of the non-invasive imaging methods, magnetic resonance imaging (MRI) is preferred and widely applied for disease diagnosis. However, the practical application of most reported MRI contrast agents is limited by their potential toxicity and low specificity for pathological tissues. In this study, we developed a macrophage-targeting and ROS-responsive iron complex (FePM) as a T1-enhanced MRI contrast agent for inflammation imaging. The Fe(II) in FePM could be oxidized in a highly concentrated ROS environment rapidly, accompanied by clear longitudinal relaxivity (r₁) enhancement, which enabled the complex to act as a ROS-sensitive contrast agent for tumor-specific MR imaging. Cell experiments showed that FePM exhibited good biocompatibility and significant targeting specificity to macrophages. Furthermore, in vitro MRI studies demonstrated that the enhanced T1 contrast effect against macrophages could be achieved after incubating with FePM. Therefore, FePM is an ideal candidate for an inflammation-specific MRI contrast agent, which holds considerable potential for increasing contrast and improving diagnostic precision.

This study leverages statistical analysis (χ2 test of independenc and Two Proportion Z-Test) and machine learning clustering techniques—K-Modes and K-Prototypes—along with t-SNE visualization and CatBoost classification to analyze socioeconomic integration and inequality. Our analysis identifies five distinct population segments, revealing that while citizenship status shows no association with workforce participation, significant disparities exist in access to employer-sponsored health insurance. Non-citizens are disproportionately concentrated in precarious employment without benefits, highlighting systemic inequalities in healthcare access. These findings underscore the urgent need for policies that ensure equitable access to health benefits, regardless of citizenship status.

Hepatocellular Carcinoma (HCC) occurs when malignant tumors grow on the liver and has many risk factors including HBV infection and old age. It is the most common type of primary liver cancer and is often seen in Western countries, East Asia, and Northwest Africa regions. One gene associated with the development of HCC is the Negative Elongation Factor E (NELFE), a proto-oncogene encoding important RNA-binding proteins in the multi-subunit NELF complex responsible for RNA polymerase II pausing during DNA transcription. NELFE is also heavily involved in the regulation and enhancement of MYC signaling, another proto-oncogene coding for transcription factors. The dysregulation of both NELFE and MYC genes may lead to the progression of tumors. However, as MYC controls many essential cellular processes and cannot be targeted, NELFE appears to be a promising target for advancing HCC treatments.

Immigrants make up 15% of the U.S. population, with roots stretching back to the colonial era in the 1600s. For centuries, they have been instrumental in driving economic growth through their labor and perseverance. However, recent policies—such as the mass deportations under President Trump—have deepened systemic inequities. This study explores how immigrants navigate barriers in healthcare, employment, and education, drawing on interviews with four Latino and Asian immigrants. Findings highlight structural challenges linked to immigration status, including workplace exploitation, social discrimination, and gaps in rights awareness—some due to policy loopholes, others due to limited knowledge of legal protections. The study calls on policymakers and society to address these injustices while acknowledging immigrants’ vital contributions, and emphasizes the importance of immigrant communities staying informed about their rights.

Recent ankle rehabilitation research has introduced the use of robotic exoskeletons to enhance muscle strength and correct gait. Fixed-position robots assist in early-stage training but cannot be used while walking. Wearable exoskeletons support walking but struggle with foot rotation along the z-axis. Full lower-limb devices offer broader support but are bulky and not specialized for ankle injuries, making them less convenient. This research aims to address these limitations.

Hepatocellular carcinoma (HCC) is one of the most common types of liver cancer, and is currently one of the fastest increasing types of cancer in the United States. However, its heterogeneity causes major challenges in finding clinical treatments. Negative Elongation Factor E presence has shown to connect with growth of tumors. This paper explores how antisense oligonucleotides (ASOs) can alter the splicing, expression, and stability of the NELFE gene, and how it can be leveraged to decrease harmful NELFE levels in cancer cell. Using Hep3B, Huh1, and Huh7 human cell lines, this research attemps to turn a natural genetic vulnerability into a precision treatment tool via ASO-induced exon skipping, harnessed therapeutically to potentially slowing cancer progression. Lower NELFE disrupts the NELF complex, potentially impairing transcriptional pausing in cancer cells. Moreover, our created i9 and e10 ASOs successfully targeted intron 9 or exon 10 of NELFE and mimicked a naturally occurring single nucleotide polymorphism (SNP) that drives exon 10 skipping to reduce NELFE protein expression.

To address the clinical practioners' low accuracy on the early diagnosis of the Alzheimer's Disease, the author uses an unprecedented method of combining a state-of-the-art image recognition model, a Vision Transformer (ViT), with a saliency map, Grad-CAM to increase human understanding and interpretability of the predicted results, successfully achieving 99% accuracy and making a revolutionary contribution to the early diagnosis of Alzheimer's Disease.