Lenacapavir (LEN) is a first-in-class capsid inhibitor (CAI) that targets multiple stages of the HIV-1 lifecycle, showing efficacy in heavily treatment-experienced (HTE) individuals with multidrug-resistance (MDR) and in pre-exposure prophylaxis (PrEP). This study aimed to characterize a novel home-made next-generation sequencing (NGS) protocol targeting HIV-1 capsid (CA) region using both HIV-1 RNA from plasma and HIV-1 DNA from peripheral-blood-mononuclear-cells (PBMCs). Accordingly, 60 samples (41 HIV-1 RNA, 19 HIV-1 DNA) with various HIV-1 subtypes and viremia levels were tested. Molecular amplification was successful in 83.3% of cases (75.6% HIV-1 RNA and 100% HIV-1 DNA), with sequencing achieved in 92.0% of amplified samples (87.1% HIV-1 RNA and 100% HIV-1 DNA). The protocol showed high NGS performance with HIV-1 RNA samples with viremia >500 copies/mL (92.6%) and a slight impact of subtype-associated variability (subtype B: amplification and sequencing 86.0% and 91.9%; non-B: 76.5% and 92.3%, respectively). Reproducibility was fully confirmed by pairwise similarity analyses at 10% and 20% frequency cutoff, upon reprocessing 13 HIV-1 RNA samples. This protocol provides an important tool for personalized HIV-1 treatment with CAI-based strategies, enabling efficient characterization of LEN resistance mutations in the CA region across different HIV-1 subtypes, using both DNA and RNA samples.

With the wide application of Lithium-ion batteries (LIBs) in consumer electronics, energy storage systems and electric vehicles, improving the energy density, cycle stability and safety of the batteries has become a key direction of research. Alloy anodes have become a strong candidate for anode materials for LIBs due to their high theoretical capacity and better electrochemical performance. However, alloy anodes face challenges such as volume expansion, structural instability, and degradation of cycling performance in practical applications. This paper systematically reviews the research progress of alloy anodes for LIBs, firstly introduces the lithium-ion reaction mechanism of alloy anodes, analyzes the classification and properties of different alloy anodes, and then focuses on the current major design strategies of alloy anodes, including nano- and microstructure tuning, coating and surface modification, structural tuning, and composite material applications. Finally, the future development direction of alloy anodes is envisioned, aiming to provide theoretical guidance and technical support for the optimized design of anode materials for LIBs.

Trait-based approaches have revolutionized ecology by enabling the characterization of biodiversity through species’ ecological strategies. The rapid development of multiple databases has shifted the focus from data availability to the critical evaluation of trait types to explore the functional diversity of taxonomic groups. Central to this approach is the construction of a functional space, typically built by aggregating available traits into a unique multivariate framework. However, such trait aggregation may lead to ecologically unbalanced representations, where statistical variance is dominated by a subset of traits (e.g., body size), thereby masking functional strategies such as diet or reproduction. We here argue for shifting trait-based approaches from a unique functional space to multiple, ecologically explicit trait spaces, each representing a specific aspect of species’ ecological roles. Using birds as a case study, we show how this framework enhances a better understanding of biogeographic patterns and provides more targeted insights about extinction risks. We advocate for the adoption of function-related trait spaces as a foundation for trait-based ecology and conservation, offering greater ecological resolution than aggregated global indices.

As the footprint from human populations increases, the associated modification and conversion of natural landscapes in a changing climate places significant pressure on terrestrial wildlife. Since areas of high biodiversity are most affected by urbanisation, there is a need to identify future challenges for species in these regions in the context of intensifying climate change. We investigated habitat dynamics for seven macropod species found in the rapidly urbanising, biodiverse Southeast Queensland (SEQ) region of Australia. Habitat suitability was modelled using presence-only occurrence data in combination with bioclimatic and landscape variables. We evaluated a ‘balanced’ Random Forest algorithm to fit distribution models, predict potential areas of current distribution, and highlight factors that may influence current and future conservation management. Over one third of predicted current suitable habitat for eastern grey kangaroos, swamp wallabies and red-necked wallabies is within the urban footprint, a greater amount than is in protected areas. Conversely, most current suitable habitats for the other species were predicted to occur in protected areas. Worryingly, a decline in suitable habitat (83-96% reduction) is projected for all seven species under future climate scenarios. Our results reveal the vulnerability of macropods in the region which face compounded threats from urbanisation and climate-induced habitat loss. This study’s findings highlight a complex set of factors that could hinder macropod species’ adaptability to future environmental changes, elevating ‘least concern’ species to ‘of concern’. Combined pressures from climate change, urbanisation, and habitat loss necessitate a broad, adaptive approach to wildlife conservation in human-dominated landscapes.

Advances in fine-scale movement modeling of soaring birds can aid efforts to understand and resolve the impacts of anthropogenic activities on such birds. Soaring birds often rely on underlying terrain and low-altitude updrafts to govern their flights at rotor-swept altitudes (≤200 m above ground level), which puts them at risk of collision with turbines. We developed a data-driven Markov model at 1-s resolution that predicts the fine-scale flight behavior of golden eagles (_Aquila chrysaetos_) as a function of ecological covariates at the current location as well as those within an eagle’s line of sight. We only considered ecological covariates that are readily available in real-time (ground elevation and wind conditions). Latent factors (age, sex, species, behavioral intent, migratory status) were intentionally left out of the model. We calibrated the model using golden eagle telemetry data collected in two different ecoregions of the United States. Given a starting location, the calibrated model simulates multiple stochastic 3D paths to produce a time-explicit and spatially explicit risk map of turbine collisions. We discovered an empirical relation between the rate of heading and the orographic updraft conditions within an eagle’s line of sight. Our model performed most effectively when predicting predominantly-soaring flights at rotor-swept altitudes during wind conditions in which turbines are likely to be operational. The calibrated model could be used in concert with automated eagle detection and turbine curtailment technologies. Specifically, once an eagle is detected by those systems, our model could then provide accurate predictions of turbines the eagle is likely to interact with in the near term.

Understanding a species’ genetic population structure is fundamental for determining its conservation and management units. Bull trout (Salvelinus confluentus), a charr native to northwestern North America, are experiencing significant population declines across their range. In Alberta, bull trout are classified as Threatened under Alberta’s Wildlife Act, but knowledge of their genetic population structure is limited. We aimed to assess bull trout population structure in Alberta using genetic markers from a RADcapture SNP panel. Our sampling spanned 24 Hydrologic Unit Code 8 (HUC8) watersheds. One of our goals was to evaluate support for two previously-proposed bull trout Designatable Units (DUs) in Alberta: the Western Arctic DU and the Saskatchewan-Nelson DU. We found notable population structure and high differentiation (FST = 0.400) between these two DUs, suggesting two discreet populations that correspond to the northern and southern biogeographical zones of Alberta. We conducted ad hoc population differentiation analyses using ADMIXTURE, which revealed that bull trout have a hierarchical (or nested) population structure. Our results inform management of the species and suggest considering various scales of population structure to protect local adaptations and genetic diversity across relevant spatial scales.

Background: Hepatocellular carcinoma (HCC) is a common primary liver malignancy. Despite advancements in treatment, HCC often has a poor prognosis because of frequent recurrence and metastasis. Hematogenous metastasis to the gastrointestinal tract is uncommon and metastasis to the small intestine is particularly rare. Method: We present the case of a 72-year-old man with HCC who developed small bowel metastasis and intussusception. A literature review was conducted using the keywords “hepatocellular carcinoma,” “small bowel metastasis,” and “gastrointestinal tract metastasis” in the MEDLINE (PubMed) database. Non-English language reports were excluded. Results: Fifteen cases of HCC metastasis to the small intestine were retrieved from the literature, with two cases diagnosed post-mortem. Of the 13 reported cases and the present case, 10 cases involved male patients. The most common symptom was gastrointestinal bleeding, which occurred in 50% of cases, followed by elevated tumor markers and bowel obstruction. Imaging modalities such as computed tomography and positron emission tomography were typically used for a diagnosis, whereas endoscopic examination was used for detecting duodenal tumors. The metastatic tumors exhibited various morphologies across all three segments of the small intestine. Portal vein thrombosis or tumor invasion was reported in only one-half of the cases. Surgical resection remains the most effective treatment for isolated small bowel metastases. Conclusion: Small intestine metastasis from HCC, although rare, should be considered in patients with gastrointestinal symptoms or unexplained elevated tumor markers. Surgical resection is the most effective treatment approach, with minimally invasive and endoscopic techniques available for select cases.

The word “avian” could be interchanged with “bird” referring to warm-blooded vertebrates in the Aves class. They have feathers and lightweight skeleton modified for flight, could be as small as Bee Hummingbird (5.5cm) or as large as Ostrich (2.8m) yet, lay hard-shelled eggs which are incubated to produce hatchlings. They are found worldwide but densely populated in South America, providing crucial services for healthy environment and human well-being with regard to pollination, seed dispersal, nutrient cycling, pest control, scavenging hence, could boost ecotourism. Their ecosystems mostly terrestrial, aquatic and more recently “technoecosystems” where they inhabit woodland, water, scrub-shrub and burrows in trees or soils, have been studied with tremendous achievement through high-tech facilities. Their peculiar flight, biochemical and defence mechanisms, have generated new understanding through, integrated investigation leading to new theories on avian species. With these distinguishing characteristics and economic potentials, ornithologists still lament that many of these birds, face existence pressures, predominantly habitat loss, climate change, bush burning, urbanization, hunting, poaching and extinction. Consequently, a new synthesis concentrating on avian ecological preservation awareness and economy-prudent measures to restore and protect avian species, becomes imperative. Hence, this paper provided insights on avian ecology adopting novel approaches.

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Cystic fibrosis (CF) is a severe genetic disorder caused by mutations in the CFTR gene, leading to impaired chloride transport and multi-organ epithelial dysfunction. The advent of CFTR modulators, particularly the triple therapy elexacaftor/tezacaftor/ivacaftor (ETI), has revolutionized CF treatment. However, inter-individual variability in therapeutic response remains a challenge, often linked to pharmacokinetic (PK) differences. While plasma remains the standard for PK studies, its invasiveness limits its utility, especially in pediatric and outpatient settings. In this study, we advanced a multidimensional PK framework by combining plasma and dried blood spot (DBS) analysis with novel, non-invasive sampling from nasal swabs (NAS) and sweat. Building on validated LC-MS/MS protocols, we demonstrated that DBS offers a reliable surrogate for plasma in monitoring systemic drug exposure. Moreover, we introduced new methods for detecting ETI concentrations in NAS and sweat, enabling the assessment of local drug distribution in airway surfaces and sweat glands-tissues critical to CF pathology. This truly minimally invasive integrative approach supports a more personalized and mechanistically informed strategy for therapeutic drug monitoring in CF, potentially enhancing the prediction of clinical response to CFTR modulation.

Accurate multi-variate meteorological time series forecasting, particularly for wind speed, is crucial for effective renewable energy integration. However, existing deep learning models often struggle to simultaneously capture complex long-range temporal dependencies and intricate inter-variable relationships. To address these limitations, this research introduces and evaluates a novel hybrid architecture that combines Spatio-Temporal Convolutional Sequence to Sequence models with Transformer encoders. We investigated both serial and parallel configurations, with the parallel design uniquely employing cross-attention for enhanced feature fusion. Our experiments were conducted on regionally aggregated multi-variate time series data from Southeast Asia, where input spatial dimensions were treated as H=1 and W=1 to focus on temporal and inter-variable dynamics. The parallel Spatio-Temporal Convolutional Sequence to Sequence-Transformer model achieved a Root Mean Squared Error of 0.1064 and a Mean Absolute Error of 0.0858 in wind speed prediction, significantly outperforming various baseline models. These results affirm the substantial benefits of explicitly modeling long-range temporal dependencies and effectively fusing diverse features within multi-variate time series. While this study demonstrates the architecture’s efficacy for regionally focused time series, its design inherently possesses the potential for broader spatio-temporal applications on grid-based data.

IntroductionImmune checkpoint inhibitors (ICIs) are approved for the management of solid and hematologic malignancies and have significantly improved cancer-related care. ICIs augment the intrinsic immunity through various mechanisms including targeting programmed cell death protein 1 (PD-1), cytotoxic T-lymphocyte-associated antigen 4 (CTLA-4), and ligand proteins on tumor cells. The combined effects of ICIs block the inhibition of T-cells and allow them to kill cancer cells. Although significant antitumor efficacy has been reported, a wide range of life-threatening inflammatory and autoimmune side effects have been associated with ICIs [1].ICI-induced myocarditis with myositis/myasthenia gravis overlap syndrome is a rare adverse effect of ICI therapy and carries a high mortality [2]. Antibodies are used in diagnostics and the disease is known to confer pathogenicity through certain molecular targets: acetylcholine receptor antibody [3], muscle-specific receptor tyrosine kinase [4], and numerous extracellular and intracellular antibodies [5]. However, 10-15% of patients with ICI-induced myasthenia gravis may be seronegative and antibody detection has proven invaluable in measuring disease severity in patients with myasthenia gravis [6]. Ultimately, the diagnosis is clinical while novel antigenic targets and their diagnostic relevance continues to be studied. We present two cases of ICI-induced myocarditis with myositis/myasthenia gravis overlap syndrome and review current literature to emphasize its severity and management.

The removal of 2-methylisoborneol and geosmin from drinking water is a persistent challenge due to their resistance to treatment methods. This study employs a multi-criteria decision-making approach, integrating the AHP, TOPSIS, and VIKOR, to evaluate five treatment alternatives: activated carbon adsorption (A1), modified activated carbon adsorption (A2), peroxone oxidation (A3), integrated original activated carbon and peroxone process (A4), and integrated modified activated carbon and peroxone process (A5). The assessment was conducted across seven criteria, including technical performance, environmental sustainability, economic feasibility, operational feasibility, usability & monitoring, safety & health risks, and adaptability & suitability. Results indicate that A2 exhibits the highest removal efficiency, while A3 offers the fastest degradation but has high chemical demands and safety risks. AHP and TOPSIS ranked A2 as the most favorable, suggesting that it provides a balanced performance across multiple criteria. Future studies should explore the integration of machine learning techniques to enhance decision-making reliability.

Introduction Dental implant displacement into the maxillary sinus is a rare but clinically significant complication in implant dentistry. The posterior maxilla poses challenges due to its proximity to the maxillary sinus, poor bone quality, and sinus pneumatization. Implant migration may occur, particularly during surgery or after placement, due to factors such as inadequate primary stability, bone resorption, changes in nasal air pressure, or iatrogenic factors related to the surgeon’s experience level (1). The Schneiderian membrane, which lines the maxillary sinus, demonstrates ciliary activity facilitating the transport of mucus toward the ostium and contributing to the maintenance of sinus homeostasis. However, these ciliary forces are insufficient to mobilize a dental implant once displaced. In contrast, mechanical forces generated by repetitive head movements can lead to positional changes of the implant within the sinus, potentially resulting in complications such as maxillary sinusitis, oroantral fistula, or migration to adjacent structures, including the ostium, nasal cavity, or orbit (2). The implant’s final position, determined by head movements, dictates the appropriate surgical approach for retrieval (3).Several techniques have been described in the literature for implant removal such as the Caldwell-Luc procedure, which creates a window in the anterior sinus wall, the bone lid technique, and the lateral antrostomy technique or its modifications are commonly utilized (2,3). In recent years, endoscopic approaches including transnasal and transoral methods are increasingly favored for their minimal invasiveness, superior visibility, and reduced postoperative complications (4).This report presents a rare case of implant migration within the maxillary sinus, emphasizing the dynamic displacement potential caused by excessive head movement (5). On the day of incident, periapical radiography identified the implant at the sinus floor, whereas Cone-Beam Computed Tomography (CBCT) performed a week later revealed its translocation to the ostium, likely due to patient mobility (6,7). Despite the challenges posed by this movement, the implant was successfully retrieved intraorally using indirect vision with rhodium dental mirrors and a custom-modified dental probe. The probe, adapted from a standard dental tool, was pre-shaped to securely engage the implant’s threads and extend to the ostium for effective retrieval. This case highlights the critical importance of comprehensive preoperative planning, anticipation of potential implant migration routes, and the use of patient-specific retrieval tools for successful intraoral management of displaced implants within the maxillary sinus.

Online HD map construction serves as a critical infrastructure for autonomous driving, providing precise geometric and semantic priors for downstream planning modules. While existing methods have improved accuracy, they remain challenged by disordered vectorized sequences and topological distortions caused by noisy sensor inputs and fragmented decoding mechanisms. To address these limitations, we propose Hierarchical Dual-Path Framework for Robust HD Map Construction via Median-Enhanced Attention and Geometric-Semantic Interaction(HDP-Map), a dual-path framework featuring hierarchical semantic-geometric interaction with two key innovations: Median-enhanced Multi-scale Spatial Attention (M2SA): A noise-robust feature fusion module integrating differentiable median pooling and multi-scale convolutional operations, effectively suppressing environmental interference while enhancing local discriminability for elongated structures like lane markings. Hierarchical Interaction Decoder: A transformer-based architecture that synchronously optimizes global topology consistency and local geometric continuity through bidirectional refinement of semantic-level queries and topology-level queries. Extensive experiments demonstrate state-of-the-art performance on nuScenes and Argoverse2 benchmarks: HDP-Map achieves 67.3% mAP on nuScenes, surpassing MapTR by +5.0% . HDP-Mapv2 attains 69.4% mAP on Argoverse2, outperforming MapTRv2 by +5.8% with 41% fewer topological fractures. The framework provides a deployment-friendly solution for real-time HD map construction, balancing precision and efficiency in complex urban scenarios.

：This paper proposes a fixed-time tracking control scheme for unmanned surface vessels based on nonsingular fast terminal sliding mode (NFTSM) and disturbance observer. Firstly, a fixed-time convergent virtual control law is proposed, which improves the convergence speed of position errors when the velocity error tend to zero. Secondly, a fixed-time NFTSM control strategy is proposed based on the difference between the actual ship velocity and the virtual desired velocity, which eliminate the singularity of the system and ensure that the ship converges to the desired trajectory within a fixed time. Thirdly, a disturbance observer is utilized to estimate and compensate the unknown time-varying environmental disturbances. And the Lyapunov theory are introduced to guarantee the stability of the system. Finally, simulation results demonstrate that the designed NFTSM control strategy can accurately estimate different external environmental disturbances, improve system error convergence speed, and exhibit high trajectory tracking accuracy.

This study proposes a robust and high-fidelity numerical framework for solving the integral form of the one-dimensional (1D) unsteady heat conduction (HC) equation. The framework is built upon the spectral Galerkin method utilizing Chebyshev and Hermite polynomials as orthogonal basis functions for spatial discretization By reformulating the classical parabolic heat equation into an equivalent integral representation using Green’s function and the Laplace transform the problem gains enhanced smoothness and numerical stability-particularly in the presence of sharp gradients or boundary layers (Atkinson 1997; Polyanin & Manzhirov 2008) The spectral Galerkin method renowned for its exponential convergence when applied to smooth problems (Boyd 2001; Shen et al. 2011) was implemented using both polynomial bases Comparative numerical experiments indicate that Chebyshev polynomials exhibit superior accuracy and faster convergence compared to Hermite polynomials within bounded domains In contrast, Hermite polynomials despite their theoretical strength on unbounded intervals displayed slower convergence and higher approximation errors when constrained to finite domains. Error analyses conducted for multiple polynomial degrees confirmed the spectral nature of the convergence with Chebyshev-based solutions consistently outperforming their Hermite counterparts. As a result the study concludes that Chebyshev polynomials are the more appropriate choice for solving bounded-domain heat conduction problems using the integral Galerkin spectral method The proposed methodology not only ensures stability and high-order accuracy for classical thermal problems but also offers a promising foundation for future extensions to nonlinear time-dependent and multidimensional heat transfer systems

We present a new open source magnetotelluric inversion solver, MT GEMMIE, developed for three-dimensional inversion of large-scale datasets, both in terms of survey area, period range, and number of observations. The forward problem solver, which forms the core of any inversion algorithm, is based on a modern implementation of the volume integral equation approach and demonstrates near-linear scalability across thousands of computational cores. The main methodological innovations introduced in MT GEMMIE are: 1) a novel model parameterization strategy - the so-called non-local parameterization - which helps suppress artifacts near observation sites and significantly accelerates convergence to the inverse solution (by up to several times); 2) utilization of the recently developed version of the quasi-Newton iterative optimization method that exploits the structure of the regularized inverse problem and effectively eliminates the need for the additional iterations during line search; 3) the modeled fields interpolation technique that enables proper inverting data across a large number of periods preserving the integrity of the observed responses and their associated error estimates. The workability of the presented solver and the efficacy of the proposed techniques are confirmed by validation on a synthetic dataset and by comparison with the results of inverting real data acquired in Central Mongolia, performed by a fundamentally different inverse solver based on the finite element method.

We study the small mass limit for a class of systems described by McKean–Vlasov equations with different types of interaction potentials. Our aim is to identify the limiting equation and establish bounds on the error between solutions of the associated nonlinear kinetic Fokker–Planck equation and the limiting equation. We introduce an intermediate system through a coarse-graining map, enabling us to estimate the error between the spatial densities of the Vlasov–Fokker–Planck equation and the intermediate system in terms of the 2-Wasserstein distance. Subsequently, we derive an inequality for Wasserstein gradient flows, by quantifying the error between the intermediate system and the corresponding limiting equation. This approach requires only the weak integrability of the interaction potentials, which quantifies the small mass limit of the nonlinear Fokker–Planck system with three different types of interaction potentials: bounded and Lipschitz interaction potential, singular interaction potential, and bounded interaction potential. Moreover, our approach includes examples of singular interactions such as Riesz potential and the Coulomb potential.

Human embryonic kidney cells (HEK293) are a widespread choice for recombinant protein expression. To optimise yields, the hydrolysate Tryptone N1 (TN1) is commonly added post-transfection. TN1 is obtained by controlled enzymatic digestion of casein. As an animal by-product, TN1 faces strict regulations during cross-country shipments as compared to plant-based products. This raises the question whether plant-derived peptides are a suitable alternative to TN1. Using polyethyleneimine as a cationic polymer, we transfected HEK293-6E cells grown in suspension in serum-free medium and divided the transfectants into 4 groups. Two plant-based hydrolysates derived from pea and broad-bean, respectively, were compared with TN1 and a no-hydrolysate control group. Transfection efficiency between biological replicates, as determined by transfection of a GFP-encoding plasmid, was similar. We monitored the cultures for total cell numbers and viability at days 1, 4 and 5 post-transfection. Both plant-based hydrolysates and TN1 showed similar live cell percentages, in contrast to the no-hydrolysate control, which showed lower viability. Five days post-transfection. Expressed protein was retrieved from the serum-free culture supernatant and quantified through Western blotting using stain-free technology and total lane quantification. The plant-derived pea and broad-bean hydrolysates resulted in similar expression quantity as animal-derived TN1; all three hydrolysates were better than no hydrolysate. We conclude that plant-derived hydrolysates are a suitable replacement for TN1.

In this paper, we will be discussing hyperbolas and other related algebraic varieties in n-dimensional space with group structures defined by projection multiplication, as well as detailing some of the theory that immediately emerges.

In this paper, we will extend the fundamental group π1 from its context in topological spaces to the context of graphs. We will also give some examples of fundamental groups of certain graphs, e.g. Kn.

Plumbagin (PLB), a naphthoquinone compound exhibiting significant antitumor activity, has its clinical application limited due to cellular toxicity. This study investigated the adsorption mechanism and Raman spectroscopic properties of PLB interacting with gold clusters of varying sizes (Au 2, Au 4, Au 6, Au 8) using density functional theory (DFT). Based on the surface enhancement of Raman scattering (SERS), the orientation of the PLB molecule on the gold substrate surface was inferred, and their interactions were investigated. The results indicate that PLB adsorbs vertically onto the surface of Au n cluster via the O13 atom, forming stable complexes. Among these, the PLB-Au 4 complex exhibits the strongest binding energy (-64.80 kJ·mol -1) and the shortest bond length (2.2403 Å). Raman spectrum analysis revealed that the characteristic peaks of the complexes are ”selectively” enhanced due to changes in the local environment of the atoms closer to the Au n cluster in the molecule of PLB, induced by charge transfer effects. Furthermore, frontier molecular orbital analysis demonstrated that the introduction of Au n clusters significantly reduces the energy gap of the system (maximum reduction of 47.45%), thereby enhancing the chemical reactivity of PLB. This work provides experimental evidence and theoretical support for improving the bioavailability of PLB and developing a new drug delivery platform based on PLB combined with Au nanoparticles complex.

The significance of nanoparticles (NPs) in technological advancements is due to their adaptable characteristics and enhanced performance over their parent material. They are frequently synthesized by reducing metal ions into uncharged nanoparticles using hazardous reducing agents. However, there have been several initiatives in recent years to create green technology that uses natural resources instead of dangerous chemicals to produce nanoparticles. In green synthesis, biological methods are used for the synthesis of NPs because biological methods are eco-friendly, clean, safe, cost-effective, uncomplicated, and highly productive. Numerous biological organisms, such as bacteria, actinomycetes, fungi, algae, yeast, and plants, are used for the green synthesis of NPs. Additionally, this paper will discuss nanoparticles, including their types, traits, synthesis methods, applications, and prospects.