Cracking the Code: Enhancing Molecular Tools for Progress in Nanobiotechnology.

Nature continually refines its processes for optimal efficiency, especially within biological systems. This article explores the collaborative efforts of researchers worldwide, aiming to mimic nature's efficiency by developing smarter and more effective nanoscale technologies and biomaterials. Recent advancements highlight progress and prospects in leveraging engineered nucleic acids and proteins for specific tasks, drawing inspiration from natural functions. The focus is developing improved methods for characterizing, understanding, and reprogramming these materials to perform user-defined functions, including personalized therapeutics, targeted drug delivery approaches, engineered scaffolds, and reconfigurable nanodevices. Contributions from academia, government agencies, biotech, and medical settings offer diverse perspectives, promising a comprehensive approach to broad nanobiotechnology objectives. Encompassing topics from mRNA vaccine design to programmable protein-based nanocomputing agents, this work provides insightful perspectives on the trajectory of nanobiotechnology toward a future of enhanced biomimicry and technological innovation.

Modeling the Reactive Oxygen Species (ROS) wave in Chlamydomonas reinhardtii colonies.

Reactive oxygen species (ROS) play a crucial role as signaling molecules in both plant and animal cells, enabling rapid responses to various stimuli. Among the many cellular mechanisms used to generate and transduce ROS signals, ROS-induced-ROS release (RIRR) is emerging as an important pathway involved in the responses of various multicellular and unicellular organisms to environmental stresses. In RIRR, one cellular compartment, organelle, or cell generates or releases ROS, triggering an increased ROS production and release by another compartment, organelle, or cell, thereby giving rise to a fast propagating ROS wave. This RIRR-based signal relay has been demonstrated to facilitate mitochondria-to-mitochondria communication in animal cells and long-distance systemic signaling in plants in response to biotic and abiotic stresses. More recently, it has been discovered that different unicellular microorganism communities also exhibit a RIRR cell-to-cell signaling process triggered by a localized stress treatment. However, the precise mechanism underlying the propagation of the ROS signal among cells within these unicellular communities remained elusive. In this study, we employed a reaction-diffusion model incorporating the RIRR mechanism to analyze the propagation of ROS-mediated signals. By effectively balancing production and scavenging processes, our model successfully reproduces the experimental ROS signal velocities observed in unicellular green algae (Chlamydomonas reinhardtii) colonies grown on agar plates, furthering our understanding of intercellular ROS communication.

Efficacy and safety of metronomic oral vinorelbine and its combination therapy as second- and later-line regimens for advanced non-small-cell lung cancer: a retrospective analysis.

OBJECTIVE: This retrospective analysis aimed to evaluate the efficacy and adverse reactions of metronomic oral vinorelbine and its combination therapy as second- and later-line regimens for advanced non-small-cell lung cancer (NSCLC). METHODS: NSCLC patients undergoing metronomic oral vinorelbine as second- and later-line regimens in Fujian Cancer Hospital from October 2018 to October 2022 were enrolled, and patients' demographic and clinical characteristics were collected. The efficacy and safety of metronomic oral vinorelbine monotherapy and its combination therapy regimens were compared. RESULTS: Of 57 study subjects, 63.2% received third- and later-line therapy, with median progression-free survival (mPFS) of 4 months, overall response rate (ORR) of 10.5%, and disease control rate (DCR) of 80.7%. The incidence of therapy-related adverse events was 42.1%, and there was only one case presenting grades 3 and 4 adverse events (1.8%). Among driver gene-negative participants, vinorelbine combination therapy regimens achieved longer mPFS (4.6 vs. 1.2 months, hazards ratio = 0.11, P < 0.0001) and comparable toxicity in relative to metronomic oral vinorelbine, and metronomic oral vinorelbine combined with immune checkpoint inhibitors showed the highest response, with mPFS of 5.6 months (95% CI 4.8 to 6.4 months), ORR of 25%, and DCR of 81.3%. Among participants with gradual resistance to osimertinib, continuing osimertinib in combination with metronomic oral vinorelbine achieved mPFS of 6.3 months (95% CI 0.1 to 12.5 months) and DCR of 86.7%. CONCLUSION: Metronomic oral vinorelbine and its combination therapy regimens are favorable options as second- and later-line therapy for advanced NSCLC patients, with acceptable efficacy and tolerable toxicity. Vinorelbine combination therapy regimens show higher efficacy and comparable toxicity in relative to metronomic oral vinorelbine, and metronomic oral vinorelbine may have a synergistic effect with immunotherapy and EGFR-TKI targeted therapy.

Machine learning-inferred and energy landscape-guided analyses reveal kinetic determinants of CRISPR/Cas9 gene editing.

The CRISPR/Cas nucleases system is widely considered the most important tool in genome engineering. However, current methods for predicting on/off-target effects and designing guide RNA (gRNA) rely on purely data-driven approaches or focus solely on the system's thermal equilibrium properties. Nonetheless, experimental evidence suggests that the process is kinetically controlled rather than being in equilibrium. In this study, we utilized a vast amount of available data and combined random forest, a supervised ensemble learning algorithm, and free energy landscape analysis to investigate the kinetic pathways of R-loop formation in the CRISPR/Cas9 system and the intricate molecular interactions between DNA and the Cas9 RuvC and HNH domains. The study revealed (a) a novel three-state kinetic mechanism, (b) the unfolding of the activation state of the R-loop being the most crucial kinetic determinant and the key predictor for on- and off-target cleavage efficiencies, and (c) the nucleotides from positions +13 to +16 being the kinetically critical nucleotides. The results provide a biophysical rationale for the design of a kinetic strategy for enhancing CRISPR/Cas9 gene editing accuracy and efficiency.

Design of a Transformer Oil Viscosity, Density, and Dielectric Constant Simultaneous Measurement System Based on a Quartz Tuning Fork.

Transformer oil, crucial for transformer and power system safety, demands effective monitoring. Aiming to address the problems of expensive and bulky equipment, poor real-time performance, and single parameter detection of traditional measurement methods, this study proposes a quartz tuning fork-based simultaneous measurement system for online monitoring of the density, viscosity, and dielectric constant of transformer oil. Based on the Butterworth-Van Dyke quartz tuning fork equivalent circuit model, a working mechanism of transformer oil density, viscosity, and dielectric constant was analyzed, and a measurement model for oil samples was obtained. A miniaturized simultaneous measurement system was designed based on a dedicated chip for vector current-voltage impedance analysis for data acquisition and a Savitzky-Golay filter for data filtering. A transformer oil test platform was built to verify the simultaneous measurement system. The results showed that the system has good repeatability, and the measurement errors of density, viscosity, and dielectric constant are lower than 2.00%, 5.50%, and 3.20%, respectively. The online and offline results showed that the system meets the requirements of the condition maintenance system for online monitoring accuracy and real-time detection.

Embracing exascale computing in nucleic acid simulations.

This mini-review reports the recent advances in biomolecular simulations, particularly for nucleic acids, and provides the potential effects of the emerging exascale computing on nucleic acid simulations, emphasizing the need for advanced computational strategies to fully exploit this technological frontier. Specifically, we introduce recent breakthroughs in computer architectures for large-scale biomolecular simulations and review the simulation protocols for nucleic acids regarding force fields, enhanced sampling methods, coarse-grained models, and interactions with ligands. We also explore the integration of machine learning methods into simulations, which promises to significantly enhance the predictive modeling of biomolecules and the analysis of complex data generated by the exascale simulations. Finally, we discuss the challenges and perspectives for biomolecular simulations as we enter the dawning exascale computing era.

Kinetic pathway of HIV-1 TAR cotranscriptional folding.

The Trans-Activator Receptor (TAR) RNA, located at the 5'-end untranslated region (5' UTR) of the human immunodeficiency virus type 1 (HIV-1), is pivotal in the virus's life cycle. As the initial functional domain, it folds during the transcription of viral mRNA. Although TAR's role in recruiting the Tat protein for trans-activation is established, the detailed kinetic mechanisms at play during early transcription, especially at points of temporary transcriptional pausing, remain elusive. Moreover, the precise physical processes of transcriptional pause and subsequent escape are not fully elucidated. This study focuses on the folding kinetics of TAR and the biological implications by integrating computer simulations of RNA folding during transcription with nuclear magnetic resonance (NMR) spectroscopy data. The findings reveal insights into the folding mechanism of a non-native intermediate that triggers transcriptional pause, along with different folding pathways leading to transcriptional pause and readthrough. The profiling of the cotranscriptional folding pathway and identification of kinetic structural intermediates reveal a novel mechanism for viral transcriptional regulation, which could pave the way for new antiviral drug designs targeting kinetic cotranscriptional folding pathways in viral RNAs.

Broadband Room-Temperature Photodetection via InBiTe3 Nanosheet.

Broadband room-temperature photodetection has become a pressing need as application requirements for communication, imaging, spectroscopy, and sensing have evolved. Topological insulators (TIs) have narrow bandgap structures with a wide absorption spectral response range, which should meet the requirements of broadband detection. However, owing to their high carrier concentration and low carrier mobility resulting in poor noise equivalent power (NEP), they are generally considered unsuitable for photodetection. Here, InBiTe3 alloy nanosheet formed by doping In2Te3 into Bi2Te3(≈ 1:1) is utilized, effectively improving carrier mobility by over ten times while maintaining a narrow bandgap structure, to fabricate a broadband photodetector covering a wide response range from visible to millimeter wave (MMW). Under the synergistic multi-mechanism of the photoelectric effect in the visible-infrared region and the electromagnetic-induced potential well (EIW) effect in Terahertz band, the performance of NEP = 75 pW Hz-1/2 and response time τ ≈100 µs in visible to infrared band and the performance of NEP = 6.7 × 10-3 pW Hz-1/2, τ ≈8 µs in Terahertz region are achieved. The results demonstrate the promising prospects of topological insulator alloy (like InBiTe3) nanosheet in optoelectronic detection applications and provide a direction for the research into high-performance broadband photoelectric detectors via TIs.

EIF4A3 modulated circ_000999 promotes epithelial-mesenchymal transition in cadmium-induced malignant transformation through the miR-205-5p/ZEB1 axis.

Cadmium (Cd) is an accumulative toxic metal which poses a serious threat to human health, even in trace amounts. One of the most important steps in the pathophysiology of lung cancer (LC) is the epithelial-mesenchymal transition (EMT). In this investigation, a cell malignant transformation model was established by exposing human bronchial epithelial cells (16HBE) to a low dose of Cd for 30 weeks, after which a highly expressed circular RNA (circ_000999) was identified. Cd-induced EMT was clearly observed in rat lungs and 16HBE cells, which was further enhanced following circ_000999-overexpression. Furthermore, upregulated EIF4A3 interacted with the parental gene AGTPBP1 to promote high expression of circ_000999. Subsequent experiments confirmed that circ_000999 could regulate the EMT process by competitively binding miR-205-5p and inhibiting its activity, consequently upregulating expression of zinc finger E-box binding protein 1 (ZEB1). Importantly, the circ_000999 expression level in LC tissues was significantly increased, exhibiting a strong correlation with EMT indicators. Overall, these findings provide a new objective and research direction for reversing lung EMT and subsequent treatment and prevention of LC.

SRY-Box transcription factor 9 triggers YAP nuclear entry via direct interaction in tumors.

The translocation of YAP from the cytoplasm to the nucleus is critical for its activation and plays a key role in tumor progression. However, the precise molecular mechanisms governing the nuclear import of YAP are not fully understood. In this study, we have uncovered a crucial role of SOX9 in the activation of YAP. SOX9 promotes the nuclear translocation of YAP by direct interaction. Importantly, we have identified that the binding between Asp-125 of SOX9 and Arg-124 of YAP is essential for SOX9-YAP interaction and subsequent nuclear entry of YAP. Additionally, we have discovered a novel asymmetrical dimethylation of YAP at Arg-124 (YAP-R124me2a) catalyzed by PRMT1. YAP-R124me2a enhances the interaction between YAP and SOX9 and is associated with poor prognosis in multiple cancers. Furthermore, we disrupted the interaction between SOX9 and YAP using a competitive peptide, S-A1, which mimics an α-helix of SOX9 containing Asp-125. S-A1 significantly inhibits YAP nuclear translocation and effectively suppresses tumor growth. This study provides the first evidence of SOX9 as a pivotal regulator driving YAP nuclear translocation and presents a potential therapeutic strategy for YAP-driven human cancers by targeting SOX9-YAP interaction.

Nontarget Identification of Novel Organophosphorus Flame Retardants and Plasticizers in Indoor Air and Dust from Multiple Microenvironments in China.

The indoor environment is a typical source for organophosphorus flame retardants and plasticizers (OPFRs), yet the source characteristics of OPFRs in different microenvironments remain less clear. This study collected 109 indoor air samples and 34 paired indoor dust samples from 4 typical microenvironments within a university in Tianjin, China, including the dormitory, office, library, and information center. 29 target OPFRs were analyzed, and novel organophosphorus compounds (NOPs) were identified by fragment-based nontarget analysis. Target OPFRs exhibited the highest air and dust concentrations of 46.2-234 ng/m3 and 20.4-76.0 µg/g, respectively, in the information center, where chlorinated OPFRs were dominant. Triphenyl phosphate (TPHP) was the primary OPFR in office air, while tris(2-chloroethyl) phosphate dominated in the dust. TPHP was predominant in the library. Triethyl phosphate (TEP) was ubiquitous in the dormitory, and tris(2-butoxyethyl) phosphate was particularly high in the dust. 9 of 25 NOPs were identified for the first time, mainly from the information center and office, such as bis(chloropropyl) 2,3-dichloropropyl phosphate. Diphenyl phosphinic acid, two hydroxylated and methylated metabolites of tris(2,4-ditert-butylphenyl) phosphite (AO168), and a dimer phosphate were newly reported in the indoor environment. NOPs were widely associated with target OPFRs, and their human exposure risk and environmental behaviors warrant further study.

Expert consensus on Prospective Precision Diagnosis and Treatment Strategies for Osteoporotic Fractures.

Osteoporotic fractures are the most severe complications of osteoporosis, characterized by poor bone quality, difficult realignment and fixation, slow fracture healing, and a high risk of recurrence. Clinically managing these fractures is relatively challenging, and in the context of rapid aging, they pose significant social hazards. The rapid advancement of disciplines such as biophysics and biochemistry brings new opportunities for future medical diagnosis and treatment. However, there has been limited attention to precision diagnosis and treatment strategies for osteoporotic fractures both domestically and internationally. In response to this, the Chinese Medical Association Orthopaedic Branch Youth Osteoporosis Group, Chinese Geriatrics Society Geriatric Orthopaedics Committee, Chinese Medical Doctor Association Orthopaedic Physicians Branch Youth Committee Osteoporosis Group, and Shanghai Association of Integrated Traditional Chinese and Western Medicine Osteoporosis Professional Committee have collaborated to develop this consensus. It aims to elucidate emerging technologies that may play a pivotal role in both diagnosis and treatment, advocating for clinicians to embrace interdisciplinary approaches and incorporate these new technologies into their practice. Ultimately, the goal is to improve the prognosis and quality of life for elderly patients with osteoporotic fractures.

Discovery of a Covalent Inhibitor Selectively Targeting the Autophosphorylation Site of c-Src Kinase.

Nonreceptor tyrosine kinase c-Src plays a crucial role in cell signaling and contributes to tumor progression. However, the development of selective c-Src inhibitors turns out to be challenging. In our previous study, we performed posttranslational modification-inspired drug design (PTMI-DD) to provide a plausible way for designing selective kinase inhibitors. In this study, after identifying a unique pocket comprising a less conserved cysteine and an autophosphorylation site in c-Src as well as a promiscuous covalent inhibitor, chemical optimization was performed to obtain (R)-LW-Srci-8 with nearly 75-fold improved potency (IC50 = 35.83 ± 7.21 nM). Crystallographic studies revealed the critical C-F···C═O interactions that may contribute to tight binding. The kinact and Ki values validated the improved binding affinity and decreased warhead reactivity of (R)-LW-Srci-8 for c-Src. Notably, in vitro tyrosine kinase profiling and cellular activity-based protein profiling (ABPP) cooperatively indicated a specific inhibition of c-Src by (R)-LW-Srci-8. Intriguingly, (R)-LW-Srci-8 preferentially binds to inactive c-Src with unphosphorylated Y419 both in vitro and in cells, subsequently disrupting the autophosphorylation. Collectively, our study demonstrated the feasibility of developing selective kinase inhibitors by cotargeting a nucleophilic residue and a posttranslational modification site and providing a chemical probe for c-Src functional studies.

An analysis of reported cases shoulder injury related to vaccine administration of after COVID-19 vaccination.

To prevent COVID-19, the COVID-19 vaccine has been widely administered worldwide, but various complications accompany this vaccine. The aim of this study was to investigate the demographic patterns, clinical features, diagnostic findings, and treatment outcomes associated with shoulder injury related to vaccine administration (SIRVA). This study examined 22 patients with SIRVA following COVID-19 vaccination from the Web of Science (WOS) and PubMed databases. The patients were categorized based on sex, age, type of COVID-19 vaccine received, dose administered, latency of symptom onset, and the presence of specific clinical manifestations. Patients, evenly distributed by sex (12 females, 10 males), and aged 21 to 84 years (mean age 46.6), were analyzed. SIRVA cases were reported across all age groups. The Pfizer - BioNTech COVID-19 vaccine had the highest incidence (n = 8), followed by the Oxford/AstraZeneca COVID-19 vaccine (n = 4). Symptoms, primarily shoulder pain (n = 22) and shoulder mobility disorders (n = 18), occurred within three days post-vaccination. Some patients also reported shoulder swelling (n = 5) and fever (n = 2). Imaging revealed nonspecific X-ray findings, supraspinatus tendon calcification (n = 2), and shoulder edema and inflammation on MRI (n = 12). This study provides insights into the clinical aspects of SIRVA related to COVID-19 vaccination. Recognition and appropriate management of these complications are crucial for optimal patient outcomes.

Bruceantinol targeting STAT3 exerts promising antitumor effects in in vitro and in vivo osteosarcoma models.

Bruceantinol (BOL) is a quassinoid compound found in the fruits of Brucea javanica. Previous research has highlighted the manifold physiological and pharmacological activities of BOL. Notably, BOL has demonstrated antitumor cytotoxic and antibacterial effects, lending support to its potential as a promising therapeutic agent for various diseases. Despite being recognized as a potent antitumor inhibitor in multiple cancer types, its efficacy against osteosarcoma (OS) has not been elucidated. In this work, we investigated the antitumor properties of BOL against OS. Our findings showed that BOL significantly decreased the proliferation and migration of OS cells, induced apoptosis, and caused cell death without affecting the cell cycle. We further confirmed that BOL potently suppressed tumor growth in vivo. Mechanismly, we discovered that BOL directly bound to STAT3, and prevent the activation of STAT3 signaling at low nanomolar concentrations. Overall, our study demonstrated that BOL potently inhibited the growth and metastasis of OS, and efficiently suppressed STAT3 signaling pathway. These results suggest that BOL could be a promising therapeutic candidate for OS.

Advances in machine-learning approaches to RNA-targeted drug design.

RNA molecules play multifaceted functional and regulatory roles within cells and have garnered significant attention in recent years as promising therapeutic targets. With remarkable successes achieved by artificial intelligence (AI) in different fields such as computer vision and natural language processing, there is a growing imperative to harness AI's potential in computer-aided drug design (CADD) to discover novel drug compounds that target RNA. Although machine-learning (ML) approaches have been widely adopted in the discovery of small molecules targeting proteins, the application of ML approaches to model interactions between RNA and small molecule is still in its infancy. Compared to protein-targeted drug discovery, the major challenges in ML-based RNA-targeted drug discovery stem from the scarcity of available data resources. With the growing interest and the development of curated databases focusing on interactions between RNA and small molecule, the field anticipates a rapid growth and the opening of a new avenue for disease treatment. In this review, we aim to provide an overview of recent advancements in computationally modeling RNA-small molecule interactions within the context of RNA-targeted drug discovery, with a particular emphasis on methodologies employing ML techniques.

Single-Atom Cu Nanozyme-Loaded Bone Scaffolds for Ferroptosis-Synergized Mild Photothermal Therapy in Osteosarcoma Treatment.

The rapid multiplication of residual tumor cells and poor reconstruction quality of new bone are considered the major challenges in the postoperative treatment of osteosarcoma. It is a promising candidate for composite bone scaffold which combines photothermal therapy (PTT) and bone regeneration induction for the local treatment of osteosarcoma. However, it is inevitable to damage the normal tissues around the tumor due to the hyperthermia of PTT, while mild heat therapy shows a limited effect on antitumor treatment as the damage can be easily repaired by stress-induced heat shock proteins (HSP). This study reports a new type of single-atom Cu nanozyme-loaded bone scaffolds, which exhibit exceptional photothermal conversion properties as well as peroxidase and glutathione oxidase mimicking activities in vitro experiments. This leads to lipid peroxidation (LPO) and reactive oxygen species (ROS) upregulation, ultimately causing ferroptosis. The accumulation of LPO and ROS also contributes to HSP70 inactivation, maximizing PTT efficiency against tumors at an appropriate therapeutic temperature and minimizing the damage to surrounding normal tissues. Further, the bone scaffold promotes bone regeneration via a continuous release of bioactive ions (Ca2+ , P5+ , Si4+ , and Cu2+ ). The results of in vivo experiments reveal that scaffolds inhibit tumor growth and promote bone repair.

Propagation of a rapid cell-to-cell H2O2 signal over long distances in a monolayer of cardiomyocyte cells.

Cell-to-cell communication plays a cardinal role in the biology of multicellular organisms. H2O2 is an important cell-to-cell signaling molecule involved in the response of mammalian cells to wounding and other stimuli. We previously identified a signaling pathway that transmits wound-induced cell-to-cell H2O2 signals within minutes over long distances, measured in centimeters, in a monolayer of cardiomyocytes. Here we report that this long-distance H2O2 signaling pathway is accompanied by enhanced accumulation of cytosolic H2O2 and altered redox state in cells along its path. We further show that it requires the production of superoxide, as well as the function of gap junctions, and that it is accompanied by changes in the abundance of hundreds of proteins in cells along its path. Our findings highlight the existence of a unique and rapid long-distance H2O2 signaling pathway that could play an important role in different inflammatory responses, wound responses/healing, cardiovascular disease, and/or other conditions.

Machine learning in RNA structure prediction: Advances and challenges.

RNA molecules play a crucial role in various biological processes, with their functionality closely tied to their structures. The remarkable advancements in machine learning techniques for protein structure prediction have shown promise in the field of RNA structure prediction. In this perspective, we discuss the advances and challenges encountered in constructing machine learning-based models for RNA structure prediction. We explore topics including model building strategies, specific challenges involved in predicting RNA secondary (2D) and tertiary (3D) structures, and approaches to these challenges. In addition, we highlight the advantages and challenges of constructing RNA language models. Given the rapid advances of machine learning techniques, we anticipate that machine learning-based models will serve as important tools for predicting RNA structures, thereby enriching our understanding of RNA structures and their corresponding functions.

The development and training effect of innovative undergraduate dental talents training project: A 6-year retrospective study.

INTRODUCTION: To summarize the development of Innovative Undergraduate Dental Talents Training Project (IUDTTP) and investigate the training effect of this extracurricular dental basic research education activity from 2015 to 2020 to obtain educational implications. MATERIALS AND METHODS: The Guanghua School of Stomatology established the IUDTTP in 2015. The authors recorded the development process and analysed the participation situation, training effect, academic performance and overall satisfaction during 2015-2020 through documental analysis, questionnaire and quiz. The t-test, chi-square test and ANOVA were used to test the difference. RESULTS: The educational goal, education module and assessment system of IUDTTP evolved and developed every year. A total of 336 students and 79 mentors attended the IUDTTP from 2015 to 2020, with the participation rate increasing from 45.1% to 73.5%. The participants exhibited favourable basic research abilities, manifesting as the increase of funded projects and published papers and satisfying quiz scores. Almost all students (94.94%) admitted their satisfaction with the IUDTTP. Moreover, the attended students surpassed the non-participants in terms of GPA, the number of acquired scholarships and outstanding graduates (p < .05). Likewise, the enrolment rate of postgraduate participants was significantly higher than non-participants. CONCLUSIONS: To date, the training effect indicated that the IUDTTP has fulfilled the education aim. It brought positive effects on promoting research interest, cultivating research capacities and enhancing academic performance. The potential deficiencies of extracurricular educational activities, including inflexibility in schedule and insufficiency in systematisms, may be remedied by more systematic educational settings in the future.