Recent Advances Research Articles

Human papillomavirus circulating tumor DNA assays as a mechanism for head and neck cancer equity in rural regions of the United States

The rates of human papillomavirus-positive oropharyngeal cancer (HPV-OPC) are rising worldwide and in the United States, particularly in rural regions including Appalachia. Rural areas face unique health challenges resulting in higher cancer incidence and mortality rates, and this includes HPV-OPC. The recent advent of highly sensitive liquid biopsies for the non-invasive detection of HPV-OPC recurrence (circulating tumor HPV DNA, HPV ctDNA) has been swiftly adopted as part of surveillance paradigms. Though knowledge gaps persist regarding its use and clinical trials are ongoing, the ease of collection and cost-effectiveness of HPV ctDNA make it more accessible for HPV-OPC survivors than usual surveillance methods of frequent exams and imaging. Herein, we discuss how implementing HPV ctDNA assays in rural regions of the United States provide one poignant example of how liquid biopsies can improve cancer care equity.

Scalable stable comb-to-tone integrated RF photonic drive for superconducting qubits

The recent advent of quantum computing has the potential to overhaul security, communications, and scientific modeling. Superconducting qubits are a leading platform that is advancing noise-tolerant intermediate-scale quantum processors. The implementation requires scaling to large numbers of superconducting qubits, circuit depths, and gate speeds, wherein high-purity RF signal generation and effective cabling transport are desirable. Fiber photonic-enhanced RF signal generation has demonstrated the principle of addressing both signal generation and transport requirements, supporting intermediate qubit numbers and robust packaging efforts; however, fiber-based approaches to RF signal distribution are often bounded by their phase instability. Here, we present a silicon photonic integrated circuit-based version of a photonic-enhanced RF signal generator that demonstrates the requisite stability, as well as a path towards the necessary signal fidelity.

Multimodal Embodiment Research of Oral Music Traditions: Electromyography in Oud Performance and Education Research of Persian Art Music

With the recent advent of research focusing on the body’s significance in music, the integration of physiological sensors in the context of empirical methodologies for music has also gained momentum. Given the recognition of covert muscular activity as a strong indicator of musical intentionality and the previously ascertained link between physical effort and various musical aspects, electromyography (EMG)—signals representing muscle activity—has also experienced a noticeable surge. While EMG technologies appear to hold good promise for sensing, capturing, and interpreting the dynamic properties of movement in music, which are considered innately linked to artistic expressive power, they also come with certain challenges, misconceptions, and predispositions. The paper engages in a critical examination regarding the utilisation of muscle force values from EMG sensors as indicators of physical effort and musical activity, particularly focusing on (the intuitively expected link to) sound levels. For this, it resides upon empirical work, namely practical insights drawn from a case study of music performance (Persian instrumental music) in the context of a music class. The findings indicate that muscle force can be explained by a small set of (six) statistically significant acoustic and movement features, the latter captured by a state-of-the-art (full-body inertial) motion capture system. However, no straightforward link to sound levels is evident.

Recent advances in the study of epitopes, allergens and immunologic cross-reactivity of edible mango

Mango (Mangifera indica L.) is a tropical fruit that is widely consumed as both fresh fruits and processed products around the world. The high incidence of mango allergy, on the other hand, has sparked widespread concern. Therefore, a summary and analysis of the current status and issues in mango allergen research can guide in-depth study on the mechanism of mango allergy and reveal effective desensitization methods. We described the incidence of fruit allergy, as well as the mechanism and clinical symptoms of mango allergy, in this review. We also looked into the structural properties of mango allergens, the effect of processing methods on mango allergens, prediction methods for mango allergen epitopes, and the current state of research on mango cross-reactive allergens and preventive measures. Finally, the research directions and ideas for the future are proposed and discussed.

Nutritional Fuelling for Microgravity Environment of Space Missions

Abstract: Since the beginning of space missions, the food systems have undergone a sea change with prolonged manned missions and permanent space habitats. We have a better understanding of physiological changes which happen in humans in space and help in adaptation to the space environment. Yet, much remains underexplored and warrants further research. Space missions today involve a considerable number of individuals operating in a microgravity environment for both short and long periods. The provision of food for such missions and managing the physio-pathological changes that affect nutritional requirements continue to be challenging. Food systems (food and beverages) used during every program to date have been shelf‐stable and were composed primarily of rehydratable or thermostabilized food items. Such foods usually have a lower hedonic value than fresh or frozen foods. Consequently, a reliable food system must provide a wide range of palatable and attractive foods as well as the tools to prepare them (through rehydration, heating, and cooling) to enhance the taste sensation of the crew. Adequate nutrition with easily accessible food is essential to this effort. To deliver nutritional recommendations to crew members for long-duration space missions, it is important to understand how nutritional status and general physiology are linked and affected by microgravity exposure. In view of this, it has been pointed out that nutritional countermeasures could rectify the physiological and behavioural anomalies during microgravity exposure. In this comprehensive narrative review, we have provided an overview of a few recent advances such as silkworm protein, good mood-vegan diet, 3-D food printing, and space garden’s produce for onboard support to food systems. It has also been found that exercise could be an addition to nutritional interventions. Areas of space exploration that require more in-depth research using ground-based bed rest models, as well as inflight microgravity conditions, are highlighted.

Recent Advancement in Multicomponent Synthesis of Fused Coumarin Derivatives.

The synthesis of coumarin derivatives has been an essential topic since its discovery in 1820. In bioactive compounds, the coumarin moiety serves as a backbone, as many such bioactive compounds with the coumarin moiety play a significant role in their bioactivities. Given this moiety's relevance, several researchers are developing fused-coumarin derivatives to create new drugs. Mostly the approach done for this purpose was a multicomponent reaction based. Over the years, the multicomponent reaction has gained enormous popularity, and this approach has evolved as a replacement for conventional synthetic methods. Because of all these perspectives, we have reported the various fused-coumarin derivatives synthesized using multicomponent reactions in recent years.

Challenges in Immunomodulation for Psoriasis: Recent Advancements and Need of Therapies

Abstract: Psoriasis is a chronic immune-mediated skin disorder affecting millions worldwide. The pathogenesis of psoriasis involves dysregulated immune responses characterized by aberrant activation of T cells and proinflammatory cytokines. Immunomodulation has emerged as a promising therapeutic approach for managing psoriasis, aiming to restore immune homeostasis. However, despite significant advancements, challenges persist in developing effective immunomodulatory therapies. This abstract reviews recent developments in psoriasis immunomodulation, encompassing novel targets and therapeutic modalities. Advances in biologics targeting interleukins (IL) and their receptors, such as IL-17, IL-23, and IL-12/23, have demonstrated substantial clinical efficacy. Additionally, small molecules that inhibit Janus kinases (JAK) and phosphodiesterase 4 (PDE4) have shown promise in regulating immune responses. Despite these advancements, certain limitations hinder the success of immunomodulatory therapies. Treatment resistance, safety concerns, and high costs remain critical challenges. Furthermore, a deeper understanding of the complex immunopathogenesis of psoriasis is essential for developing targeted and personalized therapies. In conclusion, immunomodulation has revolutionized the management of psoriasis, offering remarkable improvements in patient outcomes. Continued research and innovative therapeutic strategies are needed to overcome current challenges and pave the way for more efficient, safe, and accessible treatments for psoriasis.

Targeted Treatment of Lung Cancer using Nanomaterials: Prospective and Advances

Background: Lung cancer is the second most lethal type of cancer, with a poor survival rate of 5 years. It is one of those malignant tumors that has grown most rapidly in the context of mortality and morbidity. Aim: This review article aims to provide insight into current nanotechnological approaches taken into consideration that provide advantages over conventional chemotherapy. Result and Discussion: After comparing conventional chemotherapy and nanotechnology-based therapies for lung cancer, the results showed that recent advances in nanomaterials proved to be more effective in lung cancer diagnosis, mitigation and treatment. Here, Surface-engineered smart nanocarrier- based inhalations, Bio-nanocarriers for lung cancer, gas plasma nanoparticles, and magnetic nanoparticles are discussed. Conclusion: After summarizing these nanomaterials, investigators concluded that the in-vivo and invitro effectiveness of recently developed nanoparticles was found to be better than that of conventional nanoparticles.

Current Vaccination Practice in Diabetic (Diabetes I) Patients.

The worldwide prevalence of diabetes, an endocrine condition, is rising quickly. The alarming rise of diabetes in recent years has emerged as a major contributor to premature death and illness among persons of working age. The potential use of immunomodulatory drugs to prevent diabetes has been a source of worry in light of recent advances in our understanding of the role of autoimmune responses in the development of diabetes. Vaccines can work in a variety of ways, including by eliminating autoreactive T-cells or by blocking the connections between immune cells. Most diabetes vaccines that have been created so far have only been evaluated in animal models, with just a small number having undergone successful human trials. In this article, the authors also look at the clinical trial research that are currently being conducted to create a prototype diabetes vaccine.

The Impact of Adversarial Attacks on Federated Learning: A Survey.

Federated learning (FL) has emerged as a powerful machine learning technique that enables the development of models from decentralized data sources. However, the decentralized nature of FL makes it vulnerable to adversarial attacks. In this survey, we provide a comprehensive overview of the impact of malicious attacks on FL by covering various aspects such as attack budget, visibility, and generalizability, among others. Previous surveys have primarily focused on the multiple types of attacks and defenses but failed to consider the impact of these attacks in terms of their budget, visibility, and generalizability. This survey aims to fill this gap by providing a comprehensive understanding of the attacks' effect by identifying FL attacks with low budgets, low visibility, and high impact. Additionally, we address the recent advancements in the field of adversarial defenses in FL and highlight the challenges in securing FL. The contribution of this survey is threefold: first, it provides a comprehensive and up-to-date overview of the current state of FL attacks and defenses. Second, it highlights the critical importance of considering the impact, budget, and visibility of FL attacks. Finally, we provide ten case studies and potential future directions towards improving the security and privacy of FL systems.

Text summarization with ChatGPT for drug labeling documents

Text summarization is crucial in scientific research, drug discovery and development, regulatory review, and more. This task demands domain expertise, language proficiency, semantic prowess, and conceptual skill. The recent advent of large language models (LLMs), such as ChatGPT, offers unprecedented opportunities to automate this process. We compared ChatGPT-generated summaries with those produced by human experts using FDA drug labeling documents. The labeling contains summaries of key labeling sections, making them an ideal human benchmark to evaluate ChatGPT's summarization capabilities. Analyzing >14000 summaries, we observed that ChatGPT-generated summaries closely resembled those generated by human experts. Importantly, ChatGPT exhibited even greater similarity when summarizing drug safety information. These findings highlight ChatGPT's potential to accelerate work in critical areas, including drug safety.

Goodenough–Kanamori–Anderson high-temperature ferromagnetism in tetragonal transition-metal xenes

Seminal Goodenough–Kanamori–Anderson (GKA) rules provide an inceptive understanding of the superexchange interaction of two magnetic metal ions bridged with an anion, and suggest fostered ferromagnetic interaction for orthogonal bridging bonds. However, there are no examples of two-dimensional (2D) materials with structure that optimizes the GKA arguments towards enhanced ferromagnetism and its critical temperature. Here we reveal that an ideally planar GKA ferromagnetism is indeed stable in selected tetragonal transition-metal xenes (tTMXs), with Curie temperature above 300 K found in CrC and MnC. We provide the general orbitally-resolved analysis of magnetic interactions that supports the claims and sheds light at the mechanisms dominating the magnetic exchange process in these structures. Furthermore, we propose the set of three GKA-like rules that will guarantee room temperature ferromagetnism. With recent advent of epitaxially-grown tetragonal 2D materials, our findings earmark tTMXs for facilitated spintronic and magnonic applications, or as a desirable magnetic constituent of functional 2D heterostructures.

Post‐glacial recolonization and multiple scales of secondary contact contribute to contemporary Atlantic salmon (Salmo salar) genomic variation in North America

AbstractAimIn northern environments, periods of isolation during Pleistocene glaciations and subsequent recolonization and secondary contact have had a significant influence on contemporary diversity of many species. The recent advent of high‐resolution genomic analyses allows unprecedented power to resolve genomic signatures of such events in northern species. Here, we provide the highest resolution genomic characterization of Atlantic salmon in North America to date to infer glacial refugia and the geographic scales of post‐glacial secondary contact.LocationNorth America.TaxonAtlantic salmon, Salmo salar.MethodsSamples were collected for 5455 individuals from 148 populations, encompassing the majority of the Atlantic salmon's native range in North America, from Labrador to Maine. Individuals were genotyped using a 220K single nucleotide polymorphism array aligned to the Atlantic salmon (Salmo salar) genome. Spatial genetic structure (principal component analysis, k‐means clustering, admixture) was evaluated in conjunction with genomic comparisons of these identified lineages to infer the refugia during the last glacial maximum and regions of secondary contact following recolonization.ResultsSpatial genomic analyses identified three phylogeographic groups, consistent with the northward recolonization from two southern glacial refugia in North America (a western Maritime lineage and an eastern Newfoundland and Labrador lineage), with subsequent differentiation of the eastern lineage into two separate groups. Secondary contact among these North American groups was observed within the northern Gulf of St. Lawrence, and evidence of trans‐Atlantic secondary contact was detected within the eastern Newfoundland and Labrador lineage. Comparison of groups from insular Newfoundland with those from mainland Labrador suggests genomic regions displaying high differentiation were characterized by elevated European admixture, suggesting a possible role of European secondary contact in population divergence.Main ConclusionsThese findings present the first evidence suggesting that genomic diversity in extant North American Atlantic salmon populations has resulted from allopatric isolation in two glacial refugia followed by both regional and trans‐Atlantic recolonization and secondary contact and demonstrate the power of genomic tools to resolve historical drivers of diversity in wild populations.

Surfaces of coastal biogenic structures: exploiting advanced digital design and fabrication strategies for the manufacturing of oyster reef and mussel bed surrogates

Coastal biogenic structures, formed by ecosystem engineering species, often feature rough surfaces characterized by intricate topographies and highly three-dimensional reliefs. Their surfaces are shaped by waves and tidal currents and reciprocally influence the ambient hydrodynamics, reflecting an equilibrium. Despite their significance, the impact of these surfaces on the ambient hydrodynamics remains underexplored due to limited knowledge of accurately replicating their complex topographies in experimental setups. The recent advent of advanced digital manufacturing presents an efficient means to manufacture highly complex, three-dimensional surrogate models for experimental modeling. This work explores the accurate replication of rough coastal biogenic structures for experimental modeling on the examples of an oyster reef and a mussel bed, utilizing a flexible design methodology and, for the first time, particle bed 3D printing with Selective Cement Activation (SCA) as a fabrication and manufacturing method. A workflow is proposed, which includes an iterative surrogate model development based on in-situ topographical features, requirements of the experimental setup, and parameters of the particle bed 3D printer with SCA. The results demonstrate the effectiveness of the methodology in achieving highly accurate surrogate surfaces of complex coastal biogenic structures by validation against a set of topographical features relevant to hydraulic roughness. Particle bed 3D printing with SCA proved to be a suitable method to manufacture complex surrogate surfaces for experimental modeling, offering advantages such as independence of production time from surface complexity. However, challenges persist in achieving exact comparability between the manufactured surrogate surface and the real coastal biogenic structures, particularly for surfaces with very high complexity. Nonetheless, the manufactured generic surrogate surfaces enable detailed investigations into the influence of complex coastal biogenic structures on the ambient hydrodynamics, thereby enhancing the understanding of the processes governing wave energy dissipation attenuation, turbulence production, and vertical mixing – critical for efficient application as a nature-based solution on coastal protection or restoration efforts.

Conductive Peptide-Based MXene Hydrogel as a Piezoresistive Sensor.

Wearable pressure sensors have become increasingly popular for personal healthcare and motion detection applications due to recent advances in materials science and functional nanomaterials. In this study, a novel composite hydrogel is presented as a sensitive piezoresistive sensor that can be utilized for various biomedical applications, such as wearable skin patches and integrated artificial skin that can measure pulse and blood pressure, as well as monitor sound as a self-powered microphone. The hydrogel is composed of self-assembled short peptides containing aromatic, positively- or negatively charged amino acids combined with 2D Ti3C2Tz MXene nanosheets. This material is low-cost, facile, reliable, and scalable for large areas while maintaining high sensitivity, a wide detection range, durability, oxidation stability, and biocompatibility. The bioinspired nanostructure, strong mechanical stability, and ease of functionalization make the assembled peptide-based composite MXene-hydrogel a promising and widely applicable material for use in bio-related wearable electronics.

Recent Advances of Aminopeptidases-Responsive Small-Molecular Probes for Bioimaging.

Aminopeptidases, enzymes with critical roles in human body, are emerging as vital biomarkers for metabolic processes and diseases. Aberrant aminopeptidase levels are often associated with diseases, particularly cancer. Small-molecule probes, such as fluorescent, fluorescent/photoacoustics, bioluminescent, and chemiluminescent probes, are essential tools in the study of aminopeptidases-related diseases. The fluorescent probes provide real-time insights into protein activities, offering high sensitivity in specific locations, and precise spatiotemporal results. Additionally, photoacoustic probes offer signals that are able to penetrate deeper tissues. Bioluminescent and chemiluminescent probes can enhance in vivo imaging abilities by reducing the background. This comprehensive review is focused on small-molecule probes that respond to four key aminopeptidases: aminopeptidase N, leucine aminopeptidase, Pyroglutamate aminopeptidase 1, and Prolyl Aminopeptidase, and their utilization in imaging tumors and afflicted regions. In this review, the design strategy of small-molecule probes, the variety of designs from previous studies, and the opportunities of future bioimaging applications are discussed, serving as a roadmap for future research, sparking innovations in aminopeptidase-responsive probe development, and enhancing our understanding of these enzymes in disease diagnostics and treatment.

Diagnostic performance of EUS-guided tissue acquisition for solid pancreatic lesions ≤10 mm

ABSTRACT Background and Objectives EUS tissue acquisition (EUS-TA) is the standard diagnostic method for solid pancreatic lesions (SPLs); however, there are few reports on EUS-TA results for SPLs ≤10 mm. Furthermore, given the recent advent of fine-needle biopsy, the current diagnostic accuracy of EUS-TA for SPLs ≤10 mm is unknown. This study aimed to evaluate the diagnostic accuracy and efficacy of EUS-TA for SPLs ≤10 mm. Methods We retrospectively analyzed the data of 109 patients with SPLs ≤10 mm who underwent EUS-TA. All patients underwent rapid on-site specimen evaluation. Results The median tumor diameter was 8 mm (range, 2.5–10 mm), and the technical success rate was 99.1% (108/109). Adverse events were observed in 3 patients (2.8%). The diagnostic performance was as follows: sensitivity, 90.1% (64/71); specificity, 97.3% (36/37); accuracy, 92.6% (100/108); positive predictive value, 98.5% (64/65); and negative predictive value, 83.7% (36/43). Multivariate analysis revealed that the number of punctures (odds ratio, 7.03; 95% confidence interval, 1.32–37.5; P = 0.023) and tumor type (odds ratio, 11.90; 95% confidence interval, 1.38–102.0; P = 0.024) were independent risk factors for inaccurate EUS-TA results. The diagnostic accuracy of EUS-TA for pancreatic ductal adenocarcinoma was 87.5% (14/16). No EUS-TA–related needle-tract seeding was observed in patients with pancreatic ductal adenocarcinoma during the observation period. Conclusions EUS-TA for SPLs ≤10 mm showed adequate diagnostic accuracy and was safe for use with rapid on-site specimen evaluation in all cases.

Synthesis of Deuterated Compounds by Flow Chemistry.

Development of the efficient and practical method for the synthesis of deuterated compounds which occupies the broadest area among stable isotopes is one of the most essential issues toward the industrial advance and building a sustainable society. This review describes recent advances in deuteration reactions, where the continuous flow chemistry plays pivotal roles for the successful installation of deuterium atom into diverse organic frameworks, opening new fields of isotope-based synthetic chemistry.

Strategies for the Construction of Multicyclic Phage Display Libraries.

Peptide therapeutics have gained great interest due to their multiple advantages over small molecule and antibody-based drugs. Peptide drugs are easier to synthesize, have the potential for oral bioavailability, and are large enough to target protein-protein interactions that are undruggable by small molecules. However, two major limitations have made it difficult to develop novel peptide therapeutics not derived from natural products, including the metabolic instability of peptides and the difficulty of reaching antibody-like potencies and specificities. Compared to linear and disulfide-monocyclized peptides, multicyclic peptides can provide increased conformational rigidity, enhanced metabolic stability, and higher potency in inhibiting protein-protein interactions. The identification of novel multicyclic peptide binders can be difficult, however, recent advancements in the construction of multicyclic phage libraries have greatly advanced the process of identifying novel multicyclic peptide binders for therapeutically relevant protein targets. This review will describe the current approaches used to create multicyclic peptide libraries, highlighting the novel chemistries developed and the proof-of-concept work done on validating these libraries against different protein targets.

Adversarial Danger Identification on Temporally Dynamic Graphs.

Multivariate time series forecasting plays an increasingly critical role in various applications, such as power management, smart cities, finance, and healthcare. Recent advances in temporal graph neural networks (GNNs) have shown promising results in multivariate time series forecasting due to their ability to characterize high-dimensional nonlinear correlations and temporal patterns. However, the vulnerability of deep neural networks (DNNs) constitutes serious concerns about using these models to make decisions in real-world applications. Currently, how to defend multivariate forecasting models, especially temporal GNNs, is overlooked. The existing adversarial defense studies are mostly in static and single-instance classification domains, which cannot apply to forecasting due to the generalization challenge and the contradiction issue. To bridge this gap, we propose an adversarial danger identification method for temporally dynamic graphs to effectively protect GNN-based forecasting models. Our method consists of three steps: 1) a hybrid GNN-based classifier to identify dangerous times; 2) approximate linear error propagation to identify the dangerous variates based on the high-dimensional linearity of DNNs; and 3) a scatter filter controlled by the two identification processes to reform time series with reduced feature erasure. Our experiments, including four adversarial attack methods and four state-of-the-art forecasting models, demonstrate the effectiveness of the proposed method in defending forecasting models against adversarial attacks.