Analysis Techniques Research Articles

Smart and Sustainable Crop Protection: Design and Evaluation of a Novel α-Amylase-Responsive Nanopesticide for Effective Pest Control.

In this study, an α-amylase-responsive controlled-release formulation was developed by capping polydopamine onto β-cyclodextrin-modified abamectin-loaded hollow mesoporous silica nanoparticles. The prepared Aba@HMS@CD@PDA were subjected to characterization using various analytical techniques. The findings revealed that Aba@HMS@CD@PDA, featuring a loading rate of 18.8 wt %, displayed noteworthy release behavior of abamectin in the presence of α-amylase. In comparison to abamectin EC, Aba@HMS@CD@PDA displayed a significantly foliar affinity and improved rainfastness on lotus leaves. The results of field trail demonstrated a significantly higher control efficacy against Spodoptera litura Fabricius compared to abamectin EC at all concentrations after 7, 14, and 21 days of spaying, showcasing the remarkable persistence of Aba@HMS@CD@PDA. These results underscore the potential of Aba@HMS@CD@PDA as a novel and persistently effective strategy for sustainable on-demand crop protection. The application of nanopesticides can enhance the effectiveness and efficiency of pesticide utilization, contributing to more sustainable agricultural practices.

Private practice dietetics: A scoping review of the literature.

Private practice is one of the most rapidly growing, but under-researched employment sectors for graduate dietitians in Australia, limiting evidence-based workforce development. This scoping review examines existing international literature to gain an understanding of the current private practice workforce size, distribution, demography and workforce development considerations, including competencies, supply and demand, remuneration and professional development activities. The databases MEDLINE, EMBASE, CINAHL, EMCARE, PsycInfo (Ovid) and grey literature were systematically searched in August 2023 using key search terms to identify studies for inclusion. Articles were included if they related to private practice dietetics and described an aspect of workforce. Original research, government and organisational reports,statements of practice and websites providing governmental or organisational statistics were included. A directed content analysis and qualitative constant comparison technique were used to deductively map intelligence sources against a workforce development framework. A gap analysis was also conducted to provide a focus for future workforce development research. A total of 72 peer-reviewed and grey literature sources were included, with 65% of the studies being Australian-based publications. Private practice dietetics research interest has increased in the last decade. Despite a breadth of published sources, this review found little published data on workforce size, distribution, demography, supply, demand, continued professional development and remuneration, indicating a significant gap in the evidence base. Existing literature focuses on workforce challenges and barriers, the work of private practice dietitians, with limited exploration of competency requirements for graduate private practitioners. The literature on the private practice dietetics workforce is lacking worldwide, which constrains evidenced-based workforce development initiatives. Workforce development research across all workforce aspects is warranted to address current evidence gaps.

Bioguided Fractionation of Phyllanthus spp.: Unveiling Anticancer Potential through Metabolomic Correlation and ADMETox Insights.

Cancer remains a significant global health concern, with mortality rates steadily rising and prompting an urgent search for effective treatments. This study focuses on the medicinal properties of plants from the Phyllanthus genus, specifically Phyllanthus amarus and Phyllanthus niruri, which have shown promise in traditional medicine. Through bioguided fractionation using preparative high-performance liquid chromatography (HPLC), bioactive compounds were isolated and identified using ultra-performance liquid chromatography coupled to time-of-flight mass spectrometry (UHPLC-QTOF-MSE) and nuclear magnetic resonance (NMR) spectroscopy. Chemometric analyses such as principal component analysis (PCA) aided in understanding metabolite distribution. Biological assays demonstrated cytotoxic activities of specific fractions against cancer cell lines, notably the PhyN 4n fraction from P. niruri, which induced S-phase cell cycle arrest and apoptosis in HL60 cells. These findings underscore the anticancer potential of Phyllanthus species and lay the groundwork for future drug development efforts. The study's integration of advanced analytical techniques, chemometrics, and biological assays provides valuable insights for harnessing natural products in the fight against cancer.

Synthesis, Characterization, and Applications of Carbon Dots for Determination of Pharmacological and Biological Samples: A Review.

Carbon dots (CDs) are a novel category of carbon-based nanomaterials characterized by their small size, often less than 10 nm. CDs physical, chemical, and optical properties can be tuned using one-pot assembly. Because of their non-toxicity, biocompatibility, chemical and physical responsiveness, photo- and chemical-bleaching resistance, and low cost, nanoparticles have become incredibly versatile. They find various applications in detecting inorganic substances, bio sensing, visualizing cells, studying biological processes in live cells, and aiding in medication delivery. Additionally, CDs exhibit versatility in electronics and energy storage, making them promising candidates for applications in solar cells, light-emitting diodes, and supercapacitors. CDs are more photo stable for hours than typical fluorescent semiconductor quantum dots. Before applying CDs, they must be characterized. Techniques such as UV-VIS spectroscopy, fluorescence spectrophotometry, FT-IR, TEM, XRD, Raman spectroscopy, and NMR are commonly used to assess their photophysical and structural properties. This article review explores the synthesis, characterization applications of CDs in analytical techniques for the determination of various analytes. The article provides a detailed analysis of the different methodologies used to make nanomaterials and devices for the characterization of CDs. It also discusses the challenges that arise when using CDs in analytical techniques for detecting different analytes. The focus of this review is on accurately determining pharmaceutical and biological samples using CDs as sensing probes.

RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis.

Raman spectroscopy is a nondestructive and label-free chemical analysis technique, which plays a key role in the analysis and discovery cycle of various branches of science. Nonetheless, progress in Raman spectroscopic analysis is still impeded by the lack of software, methodological and data standardization, and the ensuing fragmentation and lack of reproducibility of analysis workflows thereof. To address these issues, we introduce RamanSPy, an open-source Python package for Raman spectroscopic research and analysis. RamanSPy provides a comprehensive library of tools for spectroscopic analysis that supports day-to-day tasks, integrative analyses, the development of methods and protocols, and the integration of advanced data analytics. RamanSPy is modular and open source, not tied to a particular technology or data format, and can be readily interfaced with the burgeoning ecosystem for data science, statistical analysis, and machine learning in Python. RamanSPy is hosted at https://github.com/barahona-research-group/RamanSPy, supplemented with extended online documentation, available at https://ramanspy.readthedocs.io, that includes tutorials, example applications, and details about the real-world research applications presented in this paper.

The COVID-19 pandemic impacted the activities of the Schistosomiasis Control Program in Brazil: is the goal of controlling the disease by 2030 at risk?

Schistosomiasis continues to represent a serious public health problem in Brazil. With the coronavirus disease 2019 (COVID-19) pandemic, several control strategies were suspended, probably compromising the goals of eradicating the disease in the country. We aimed to assess the impact of the COVID-19 pandemic on Schistosomiasis Control Program (PCE) actions in all endemic states of Brazil. We performed an ecological study using spatial analysis techniques. The PCE variables assessed were the population surveyed, the number of Kato-Katz tests, positive cases of schistosomiasis and the percentage of cases treated between 2015 and 2021. The percent change was calculated to verify if there was an increase or decrease in 2020 and 2021, along with time trend analyses provided by the Joinpoint model. Spatial distribution maps were elaborated considering the percent change. The surveyed population decreased in 2020 (-65.38%) and 2021 (-37.94%) across Brazil. There was a proportional reduction in the number of Kato-Katz tests (2020, -67.48%; 2021, -40.52%), a decrease in the percentage of positive cases (2020, -71.16%; 2021, -40.5%) and a reduction in the percentage of treated cases (2020, -72.09%; 2021, -41.67%). Time trend analyses showed a decreasing trend in most PCE variables. The PCE activities were impacted by the COVID-19 pandemic in Brazil and PCE strategies must be urgently reviewed, focusing on investments in all endemic areas.

Sequential Selective Dissolution of Coinage Metals in Recyclable Ionic Media.

Coinage metals Cu, Ag and Au are essential for modern electronics and their recycling from waste materials is becoming increasingly important to guarantee the security of their supply. Designing new sustainable and selective procedures that would substitute currently used processes is crucial. Here, we describe an unprecedented approach for the sequential dissolution of single metals from Cu, Ag and Au mixtures using biomass-derived ionic solvents and green oxidants. First, Cu can be selectively dissolved in the presence of Ag and Au with choline chloride/urea/H2O2 mixture, followed by the dissolution of Ag in lactic acid/H2O2. Finally, the metallic Au, which is not soluble in either solution above, is dissolved in choline chloride/urea/Oxone. Subsequently, the metals were simply and quantitatively recovered from dissolutions, and the solvents recycled and reused. The applicability of developed approach was demonstrated by recovering metals from electronic waste substrates such as printed circuit boards, gold fingers and solar panels. The dissolution reactions and selectivity were explored with different analytical techniques and DFT calculations. We anticipate our approach will pave a new way for contemporary and sustainable recycling of multi-metal waste substrates.

Silver Nanoparticle-Embedded Carbon Nitride: Antifungal Activity on Candida albicans and Toxicity toward Animal Cells.

The development of engineered nanomaterials has been considered a promising strategy to control oral infections. In this study, silver-embedded carbon nitrides (Ag@g-CN) were synthesized and tested against Candida albicans, investigating their antifungal action and biocompatibility in animal cells. Ag@g-CN was synthesized by a simple one-pot thermal polymerization technique and characterized by various analytical techniques. X-ray diffraction (XRD) analysis revealed slight alterations in the crystal structure of g-CN upon the incorporation of Ag. Fourier transform infrared (FT-IR) spectroscopy confirmed the presence of Ag-N bonds, indicating successful silver incorporation and potential interactions with g-CN's amino groups. UV-vis spectroscopy demonstrated a red shift in the absorption edge of Ag@g-CN compared with g-CN, attributed to the surface plasmon resonance effect of silver nanoparticles. Field emission scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM) confirmed the 2D layered sheet like morphology of both materials. The Ag 3d peaks found in X-ray photoelectron spectroscopy (XPS) confirmed the presence of metallic Ag0 nanoparticles in Ag@g-CN. The Ag@g-CN materials exhibited high antifungal activity against reference and oral clinical strains of C. albicans, with minimal inhibitory concentration (MIC) ranges between 16-256 μg/mL. The mechanism of Ag@g-CN on C. albicans was attributed to the disruption of the membrane integrity and disturbance of the biofilm. In addition, the Ag@g-CN material showed good biocompatibility in the fibroblastic cell line and in Galleria mellonella, with no apparent cytotoxicity observed at a concentration up to 1000 μg/mL. These findings demonstrate the potential of the Ag@g-CN material as an effective and safe antifungal agent for the treatment of oral fungal infections.

Optofluidic Force Induction Meets Raman Spectroscopy and Inductively Coupled Plasma-Mass Spectrometry: A New Hyphenated Technique for Comprehensive and Complementary Characterizations of Single Particles.

Nanoparticles are produced at accelerating rates, are increasingly integrated into scientific and industrial applications, and are widely discharged into the environment. Analytical techniques are required to characterize parameters such as particle number concentrations, mass and size distributions, molecular and elemental compositions, and particle stability. This is not only relevant to investigate their utility for various industrial or medical applications and for controlling the manufacturing processes but also to assess toxicity and environmental fate. Different analytical strategies aim to characterize certain facets of particles but are difficult to combine to retrieve relevant parameters coherently and to provide a more comprehensive picture. In this work, we demonstrate the first online hyphenation of optofluidic force induction (OF2i) with Raman spectroscopy and inductively coupled plasma-time-of-flight-mass spectrometry (ICP-TOFMS) to harness their complementary technology-specific advantages and to promote comprehensive particle characterizations. We optically trapped individual particles on a weakly focused vortex laser beam by aligning a microfluidic flow antiparallelly to the laser propagation direction. The position of particles in this optical trap depended on the hydrodynamic diameter and therefore enabled size calibration as well as matrix elimination. Additionally, laser light scattered on particles was analyzed in a single particle (SP) Raman spectroscopy setup for the identification of particulate species and phases. Finally, particles were characterized regarding elemental composition and their distributions in mass and size using SP ICP-TOFMS. In a proof of concept, we analyzed polystyrene-based microplastic and TiO2 nanoparticles and demonstrated the opportunities provided through the coupling of OF2i with SP Raman and SP ICP-TOFMS.

Sono-assisted photocatalytic degradation of ciprofloxacin in aquatic media using g-C3N4/MOF-based nanocomposite under visible light irradiation.

This research study is centered on the sono-assisted photocatalytic degradation of a well-known antibiotic (ciprofloxacin; CIP) in aquatic media using a g-C3N4/NH2-UiO-66 (Zr) catalyst under visible light irradiation. Initially, the catalyst was prepared by a simple method, and its physiochemical features were thoroughly analyzed by XRD, FT-IR, FE-SEM, EDX, EDS-Dot-Mapping, and UV-Vis analytical techniques. After that, the impact of several influential factors affecting the performance of the applied sono-assisted photocatalytic process such as the initial concentration of CIP, solution pH, catalyst dosage, light intensity, and ultrasound power was fully assessed, and the optimal conditions were established. After 75min of the sono-assisted photocatalytic treatment, the complete degradation of CIP (10mg/L) was accomplished under the condition as follows: g-C3N4/NH2-UiO-66 (Zr), 0.6g/L; pH, 5.0, and ultrasound power, light intensity 75 mw/cm2, 200 W/m2. Meanwhile, the photocatalytic degradation of CIP followed the pseudo-first-order kinetic model. In addition, the scavenger experiments demonstrated that OH˚ and O2°- radicals played a key role in the sono-assisted photocatalytic degradation process. It is also acknowledged that the applied catalyst was reused for five consecutive runs with a minor loss observed in its degradation efficiency. In a further experiment, a significant synergistic effect with regard to the degradation of CIP was observed once all three major parameters (visible light, ultrasound waves, and catalyst) were used in combination compared to each used alone. To sum up, it is thought that the integration of g-C3N4/MOF-based catalyst, ultrasound waves, and visible light irradiation could be potentially applied as a promising strategy for the degradation of various pharmaceuticals on account of high degradation performance, simple operation, excellent reusability, and eco-friendly approach.

A Hybrid Nanotube Stamp System in Intracellular Protein Delivery for Cancer Treatment and NMR Analytical Techniques.

In contrast to intracellular gene transfer, the direct delivery of expressed proteins is a significantly challenging yet essential technique for elucidating cellular functions, including protein complex structure, liquid-liquid phase separation, therapeutic applications, and reprogramming. In this study, we developed a hybrid nanotube (HyNT) stamp system that physically inserts the HyNTs into adhesive cells, enabling the injection of target molecules through HyNT ducts. This system demonstrates the capability to deliver multiple proteins, such as lactate oxidase (LOx) and ubiquitin (UQ), to approximately 1.8 × 107 adhesive cells with a delivery efficiency of 89.9% and a viability of 97.1%. The delivery of LOx enzyme into HeLa cancer cells induced cell death, while enzyme-delivered healthy cells remained viable. Furthermore, our stamp system can deliver an isotope-labeled UQ into adhesive cells for detection by nuclear magnetic resonance (NMR).

Single-cell sequencing advances in research on mesenchymal stem/stromal cells.

Mesenchymal stem/stromal cells (MSCs), originating from the mesoderm, represent a multifunctional stem cell population capable of differentiating into diverse cell types and exhibiting a wide range of biological functions. Despite more than half a century of research, MSCs continue to be among the most extensively studied cell types in clinical research projects globally. However, their significant heterogeneity and phenotypic instability have significantly hindered their exploration and application. Single-cell sequencing technology emerges as a powerful tool to address these challenges, offering precise dissection of complex cellular samples. It uncovers the genetic structure and gene expression status of individual contained cells on a massive scale and reveals the heterogeneity among these cells. It links the molecular characteristics of MSCs with their clinical applications, contributing to the advancement of regenerative medicine. With the development and cost reduction of single-cell analysis techniques, sequencing technology is now widely applied in fundamental research and clinical trials. This study aimed to review the application of single-cell sequencing in MSC research and assess its prospects.

The development of an organizational excellence architecture model to support the implementation of business excellence

PurposeThe purpose of this study is to address a critical gap in the existing literature on business excellence implementation. While various studies have examined different aspects of business excellence, there is still a lack of comprehensive research on the optimal organizational excellence architecture (OEA) for an award-winning business excellence journey. The absence of a unified framework has led to inconsistent practices across organizations. The aim of this research based on data collected from 50 organizations across 17 countries is to address this gap and present a refined OEA model.Design/methodology/approachThis study employed quantitative and qualitative data collection methods. Member organizations from the Global Excellence Model (GEM) Council participated through an online survey administered via the Qualtrics software platform. Quantitative data were analyzed using the SPSS and Microsoft Excel software tools, while content analysis techniques were applied to the qualitative data to gain detailed insights.FindingsThe findings refine and extend the OEA model. These contributions lead to a refined OEA definition and open avenues for future research, enriching the current understanding of BE implementation.Originality/valueThis study introduces a novel concept of OEA to the literature on business excellence implementation. The refined OEA model provides a fresh perspective on the critical components necessary for an award-winning business excellence journey. This research offers significant value to both practitioners and academics by presenting a unified approach to BE implementation, effectively addressing the previously identified gap in BE research.

Unveiling the Indian REIT narrative-qualitative insights into retail investors’ perspectives

PurposeThe present study delves into the causes of relatively lower retail participation in the Indian REIT market. Specifically, it investigates investors' attitudes and perceptions towards REITs as a unique asset class. This paper provides a comprehensive understanding of the perception and factors influencing Indian retail investors' reluctance to participate in the REIT market.Design/methodology/approachQualitative research was conducted through semi-structured interviews to gather insights from non-investors in REITs. The data were transcribed and analyzed using content analysis techniques. Finally, coding techniques were used to identify broad study themes.FindingsAccording to the study results, many retail investors are unfamiliar with REITs. Even among those knowledgeable about REITs and with a favorable view, it is not commonly seen as a feasible investment option due to its early stage, unattractive returns and limited number of REITs.Practical implicationsDeveloped countries have established REIT markets, while it is still in its infancy in developing countries such as India. Financial advisors, fund houses and the media should focus on educating investors to increase awareness.Originality/valueThe study is the first qualitative investigation into the perception of retail investors to understand the reasons for lower retail engagement in the Indian REIT market.

Online Compositional Analysis of Complex Oligomers in Biomass Degradation by High-Pressure Flow-Through Reactor Coupled with High-Resolution Mass Spectrometry.

Online analysis of the composition and evolution of complex oligomeric intermediates in biomass degradation is highly desirable to elucidate the mechanism of bond cleavage and study the effect of conditions on the selective conversion of feedstocks. However, harsh reaction conditions and complicated conversion systems pose tremendous challenges for conventional, state-of-the-art analytical techniques. Herein, we introduce a continuous and rapid compositional analysis strategy coupling a high-pressure flow-through reactor with online high-resolution mass spectrometry, which enables the molecular-level characterization of most biomass-related products throughout the conversion for over 2 h. Catalytic depolymerization of one model compound was studied, and temperature-dependent data of over 50 intermediates as well as recondensation dimers and oligomers were obtained, which have rarely been reported in the literature. Thousands of products during the flow-through conversion of birch wood with molecular weights up to 1000 Da were presented, and 8 typical lignin dimers and oligomers with various interunit linkages were identified at the molecular level, demonstrating the potential to analyze more complicated systems far beyond conventional methods, especially for complex oligomers. The continuous evolutions of different components and typical products were unveiled for the first time, providing valuable insights into the investigation of the structure, composition, and decomposition mechanism of lignocellulose as well as the influence of reaction conditions. This method leads to the previously unattained ability to probe and reveal complicated chemical compositions in high-pressure reactions and can be applied to all other high-pressure heterogeneous aqueous reactions.

Advancements in skin cancer classification: a review of machine learning techniques in clinical image analysis

AbstractEarly detection of skin cancer from skin lesion images using visual inspection can be challenging. In recent years, research in applying deep learning models to assist in the diagnosis of skin cancer has achieved impressive results. State-of-the-art techniques have shown high accuracy, sensitivity and specificity compared with dermatologists. However, the analysis of dermoscopy images with deep learning models still faces several challenges, including image segmentation, noise filtering and image capture environment inconsistency. After making the introduction to the topic, this paper firstly presents the components of machine learning-based skin cancer diagnosis. It then presents the literature review on the current advance in machine learning approaches for skin cancer classification, which covers both the traditional machine learning approaches and deep learning approaches. The paper also presents the current challenges and future directions for skin cancer classification using machine learning approaches.

Supramolecular Assemblies in Mn (II) and Zn (II) Metal–Organic Compounds Involving Phenanthroline and Benzoate: Experimental and Theoretical Studies

Two new Mn(II) and Zn(II) metal–organic compounds of 1,10-phenanthroline and methyl benzoates viz. [Mn(phen)2Cl2]2-ClBzH (1) and [Zn(4-MeBz)2(2-AmPy)2] (2) (where 4-MeBz = 4-methylbenzoate, 2-AmPy = 2-aminopyridine, phen = 1,10-phenanthroline, 2-ClBzH = 2-chlorobenzoic acid) were synthesized and characterized using elemental analysis, TGA, spectroscopic (FTIR, electronic) and single crystal X-ray diffraction techniques. The crystal structure analysis of the compounds revealed the presence of various non-covalent interactions, which provides stability to the crystal structures. The crystal structure analysis of compound 1 revealed the formation of a supramolecular dimer of 2-ClBzH enclathrate within the hexameric host cavity formed by the neighboring monomeric units. Compound 2 is a mononuclear compound of Zn(II) where flexible binding topologies of 4-CH3Bz are observed with the metal center. Moreover, various non-covalent interactions, such as lp(O)-π, lp(Cl)-π, C–H∙∙∙Cl, π-stacking interactions as well as N–H∙∙∙O, C–H∙∙∙O and C–H∙∙∙π hydrogen bonding interactions, are found to be involved in plateauing the molecular self-association of the compounds. The remarkable enclathration of the H-bonded 2-ClBzH dimer into a supramolecular cavity formed by two [Mn(phen)2Cl2] complexes were further studied theoretically using density functional theory (DFT) calculations, the non-covalent interaction (NCI) plot index and quantum theory of atoms in molecules (QTAIM) computational tools. Synergistic effects were also analyzed using molecular electrostatic potential (MEP) surface analysis.

Topological state-space estimation of functional human brain networks.

We introduce an innovative, data-driven topological data analysis (TDA) technique for estimating the state spaces of dynamically changing functional human brain networks at rest. Our method utilizes the Wasserstein distance to measure topological differences, enabling the clustering of brain networks into distinct topological states. This technique outperforms the commonly used k-means clustering in identifying brain network state spaces by effectively incorporating the temporal dynamics of the data without the need for explicit model specification. We further investigate the genetic underpinnings of these topological features using a twin study design, examining the heritability of such state changes. Our findings suggest that the topology of brain networks, particularly in their dynamic state changes, may hold significant hidden genetic information.

GhiPLATZ17 and GhiPLATZ22, zinc-dependent DNA-binding transcription factors, promote salt tolerance in upland cotton.

The utilization of transcriptome analysis, functional validation, VIGS, and DAB techniques have provided evidence that GhiPLATZ17 and GhiPLATZ22 play a pivotal role in improving the salt tolerance of upland cotton. PLATZ (Plant AT-rich sequences and zinc-binding proteins) are known to be key regulators in plant growth, development, and response to salt stress. In this study, we comprehensively analyzed the PLATZ family in ten cotton species in response to salinity stress. Gossypium herbaceum boasts 25 distinct PLATZ genes, paralleled by 24 in G. raimondii, 25 in G. arboreum, 46 in G. hirsutum, 48 in G. barbadense, 43 in G. tomentosum, 67 in G. mustelinum, 60 in G. darwinii, 46 in G. ekmanianum, and a total of 53 PLATZ genes attributed to G. stephensii. The PLATZ gene family shed light on the hybridization and allopolyploidy events that occurred during the evolutionary history of allotetraploid cotton. Ka/Ks analysis suggested that the PLATZ gene family underwent intense purifying selection during cotton evolution. Analysis of synteny and gene collinearity revealed a complex pattern of segmental and dispersed duplication events to expand PLATZ genes in cotton. Cis-acting elements and gene expressions revealed that GhiPLATZ exhibited salt stress resistance. Transcriptome analysis, functional validation, virus-induced gene silencing (VIGS), and diaminobenzidine staining (DAB) demonstrated that GhiPLATZ17 and GhiPLATZ22 enhance salt tolerance in upland cotton. The study can potentially advance our understanding of identifying salt-resistant genes in cotton.

Synthesis of nano magnetic chitosan modified with acrylamide schiff’s base for simultaneous removal of Cu(II) and Co(II) from waste water samples

ABSTRACT A magnetic nano sorbent based on the functionalization of magnetic chitosan with acrylamide was synthesized for Cu(II) and Co(II) removal from wastewater samples. To characterize the magnetic nano sorbent, they have been applied from Fourier transform infrared spectroscopic analysis (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM) techniques. The effective parameters of Cu(II) and Co(II) adsorption on magnetic nano sorbent such as pH of the solution, adsorbent dose, contact time and sample volume, were optimized. Also, the effective parameters on Cu(II) and Co(II) desorption conditions (type and volume of elution solvent) were optimized. The isotherms and kinetics models for the adsorption of Cu(II) and Co(II) on the magnetic nano sorbent were studied. The data were well-fitted with the Langmuir isotherm and pseudo-second-order model. The maximum adsorption capacities for Cu(II) and Co(II) were 165.4 and 159.9 mg g-1, respectively. Also, the thermodynamic parameters were studied. Application of magnetic nano sorbent for 4 times of use was acceptable. For the real samples, the percentage of recovery was higher than 97% and RSD (%) was between 1.4% and 2.7%. Finally, the magnetic nano sorbent exhibited high performance in removing the Cu(II) and Co(II) from wastewater samples.