Field Of Diagnostics Research Articles

Microfluidic Cartridge for Bead-Based Affinity Assays.

Within the vast field of medical biotechnology, the biopharmaceutical industry is particularly fast-growing and highly competitive, so reducing time and costs associated to process optimization becomes instrumental to ensure speed to market and, consequently, profitability. The manufacturing of biopharmaceutical products, namely, monoclonal antibodies (mAbs), relies mostly on mammalian cell culture processes, which are highly dynamic and, consequently, difficult to optimize. In this context, there is currently an unmet need of analytical methods that can be integrated at-line in a bioreactor, for systematic monitoring and quantification of key metabolites and proteins. Microfluidic-based assays have been extensively and successfully applied in the field of molecular diagnostics; however, this technology remains largely unexplored for Process Analytical Technology (PAT), despite holding great potential for the at-line measurement of different analytes in bioreactor processes, combining low reagent/molecule consumption with assay sensitivity and rapid turnaround times.Here, the fabrication and handling of a microfluidic cartridge for protein quantification using bead-based affinity assays is described. The device allows geometrical multiplexed immunodetection of specific protein analytes directly from bioreactor samples within 2.5h and minimal hands-on time. As a proof-of-concept, quantification of Chinese hamster ovary (CHO) host cell proteins (HCP) as key impurities, IgG as product of interest, and lactate dehydrogenase (LDH) as cell viability marker was demonstrated with limits of detection (LoD) in the low ng/mL range. Negligible matrix interference and no cross-reactivity between the different immunoassays on chip were found. The results highlight the potential of the miniaturized analytical method for PAT at reduced cost and complexity in comparison with sophisticated instruments that are currently the state-of-the-art in this context.

Duplex recombinase aided amplification-lateral flow dipstick assay for rapid distinction of Mycobacterium tuberculosis and Mycobacterium avium complex.

This study aims to develop a novel diagnostic approach using the recombinase aided amplification-lateral flow dipstick(RAA-LFD) assay for the distinction of Mycobacterium tuberculosis (MTB) and Mycobacterium avium complex (MAC), enabling rapid and convenient as well as accurate identification of them in clinical samples. Our study established a duplex RAA-LFD assay capable of discriminating between MTB and MAC. Based on the principles of RAA primer and probe design, specific primers and probes were developed targeting the MTB IS6110 and the MAC DT1 separately. Optimization of reaction time points and temperatures was conducted, followed by an evaluation of specificity, sensitivity, and reproducibility. The established detection method was then applied to clinical samples and compared with smear microscopy, liquid culture, LAMP, and Xpert/MTB RIF in terms of diagnostic performance. The complete workflow allows for the effective amplification of the MTB IS6110 and MAC DT1 target sequences at constant 37°C within 20min, and the amplification products can be visually observed on the LFD test strip. This method exhibits high specificity, showing no cross-reactivity with nucleic acids from M. kansassi, M. abscessus, M. gordonae, M. chelonae, M. fortuitum, M. scrofulaceum, M. malmoense, M. chimaera, M. szulgai and common respiratory pathogens. It also demonstrates high sensitivity, with a detection limit as low as 102 CFU/mL. Additionally, the method's Coefficient of Variation (CV) is less than 5%, ensuring excellent repeatability and reliability. Furthermore, clinical performance evaluations, using Xpert/MTB RIF as the gold standard, demonstrated that the duplex RAA-LFD assay achieves a sensitivity of 92.86% and a specificity of 93.75%. It is also noteworthy that the assay exhibits considerable diagnostic efficacy in smear-negative patients. Our study introduces a rapid, specific, and sensitive duplex RAA-LFD assay for the discriminatory diagnosis of MTB and MAC. This method represents a significant advancement in the field of infectious disease diagnostics, offering a valuable tool for rapid detection and management of MTB and MAC infections. The implementation of this approach in point-of-care settings could greatly enhance TB control and prevention efforts, especially in resource-limited environments.

ДІАГНОСТИКА КРИЗОВОГО СТАНУ І ЗАГРОЗИ БАНКРУТСТВА ПІДПРИЄМСТВА ТА ЇЇ МІСЦЕ В СИСТЕМІ АНТИКРИЗОВОГО УПРАВЛІННЯ

The article is devoted to the study of problems related to the theoretical and practical aspects of economic diagnostics of the сurrent condition and prospects for the deployment of crisis processes at enterprises. The topicality of the topic is determined by the fact that every enterprise faces a variety of factors that can cause the emergence and development of crisis processes; therefore, identifying and predicting these factors is important for the survival of the enterprise. Because management focused on crisis prevention is the most important prerequisite for the effectiveness of the anti-crisis management system, economic diagnostics is recognized as an important instrument and means of anti-crisis management. The article substantiates the expediency of using a set of parameters and indicators of the analysis of the financial and economic condition of the enterprise in the process of assessing its financial stability, property condition, solvency, liquidity, business activity, balanced production and sale of products, dynamics of operating costs and profit. As a key characteristic of the financial and economic state, it is proposed to consider the financial stability of the enterprise as a complex category characterizing the state, structure and directions of use of the enterprise's financial resources. It is emphasized that the assessment of the consequences of management decisions should also be considered as a field of economic diagnostics, while such diagnostics acquire special importance when the decisions relate to a certain situation related to the enterprise's acceptance of commercial risks. It is noted that the risk will be justified if the probability of obtaining income or other economic benefits is high enough, and the expected result will cover the costs associated with the risky activity. The prospects of further scientific research of the issues raised in this article are the study of the issue of improving the methodological principles and tools of economic diagnosis and improving the quality of crisis management. It is emphasized that these issues are of particular relevance in the conditions of global macroeconomic instability and uncertainty of business prospects.

Cancer Biomarkers and Precision Oncology: A Review of Recent Trends and Innovations.

The discovery of cancer-specific biomarkers has resulted in major advancements in the field of cancer diagnostics and therapeutics, therefore significantly lowering cancer-related morbidity and mortality. Cancer biomarkers can be generally classified as prognostic biomarkers that predict specific disease outcomes and predictive biomarkers that predict disease response to targeted therapeutic interventions. As research in the area of predictive biomarkers continues to grow, precision medicine becomes far more integrated in cancer treatment. This article presents a general overview on the most recent advancements in the area of cancer biomarkers, immunotherapy, artificial intelligence, and pharmacogenomics of the Middle East.

Method for Quantitative HDV RNA Detection: I, Manual Workflow (Serum and Liver Tissue) and II, Fully Automated High Throughput Workflow for Diagnostic Use.

The hepatitis delta virus (HDV) is a small RNA virus (1700 base pairs), which uses the surface proteins of the hepatitis B virus (HBV) as an envelope. Accurate and reliable quantitative detection of HDV RNA is central for scientific and translational clinical research or diagnostic purposes. However, HDV poses challenges for nucleic acid amplification techniques: (1) the circular genome displays high intramolecular base pairing; (2) high content of cytosine and guanine; and (3) enormous genomic diversity among the eight known HDV genotypes (GTs). Here, we provide step-by-step instructions for (A) a manual workflow to perform a quantitative HDV reverse transcription (RT)-PCR from serum and liver tissue and (B) a quantitative HDV RT-PCR assay with whole process control to be used for serum or plasma samples run on a fully automated system. Both assays target the conserved ribozyme region and demonstrate inclusivity for all eight HDV GTs. The choice of assay depends on the experimental needs and equipment availability. While the former is ideal for scientific research laboratories, the latter provides a useful tool in the field of translational research or diagnostics.

DiGAN Breakthrough: Advancing diabetic data analysis with innovative GAN-based imbalance correction techniques

In the rapidly evolving field of medical diagnostics, the challenge of imbalanced datasets, particularly in diabetes classification, calls for innovative solutions. The study introduces DiGAN, a groundbreaking approach that leverages the power of Generative Adversarial Networks (GAN) to revolutionize diabetes data analysis. Marking a significant departure from traditional methods, DiGAN applies GANs, typically seen in image processing, to the realm of diabetes data. This novel application is complemented by integrating the unsupervised Laplacian Score for sophisticated feature selection. The pioneering approach not only surpasses the limitations of existing techniques but also sets a new benchmark in classification accuracy with a 90% weighted F1-score, achieving a remarkable improvement of over 20% compared to conventional methods. Additionally, DiGAN demonstrates superior performance over popular SMOTE-based methods in handling extremely imbalanced datasets. This research, focusing on the integrated use of Laplacian Score, GAN, and Random Forest, stands at the forefront of diabetic classification, offering a uniquely effective and innovative solution to the long-standing data imbalance issue in medical diagnostics.

Array-based specific classification of bacterial species via ligands with dimethylamino/amino groups.

The early detection of bacterial species plays a crucial role in patient prognosis and the development of effective therapeutic regimens. This study introduces an accessible and promising colorimetric sensor array designed to classify gram-positive (G+) and gram-negative (G-) bacterial species. The classification relies on 6 chemical ligands with dimethylamino/amino groups as sensing elements and silver nanotriangles as colorimetric probes. Using these specific sensor arrays, we successfully differentiated G- and G+ bacterial species and discriminated individual bacterial strains, and the sensors exhibited remarkable reproducibility and high sensitivity. Moreover, the sensor array can identify bacterial mixtures and bacteria at varying concentrations, underscoring its versatility. In summary, this sensor array offers an effective tool for bacterial analysis with promising applications in the field of biomedical diagnostics.

Enhanced Multimodal Brain Tumor Classification in MR Images using 2D ResNet as backbone with Explicit Tumor Size Information.

It's a major public health problem of global concern that malignant gliomas tend to grow rapidly and infiltrate surrounding tissues. Accurate grading of the tumor can determine the degree of malignancy to formulate the best treatment plan, which can eliminate the tumor or limit widespread metastasis of the tumor, saving the patient's life and improving their prognosis. To more accurately predict the grading of gliomas, we proposed a novel method of combining the advantages of 2D and 3D Convolutional Neural Networks for tumor grading by multimodality on Magnetic Resonance Imaging. The core of the innovation lies in our combination of tumor 3D information extracted from multimodal data with those obtained from a 2D ResNet50 architecture. It solves both the lack of temporal-spatial information provided by 3D imaging in 2D convolutional neural networks and avoids more noise from too much information in 3D convolutional neural networks, which causes serious overfitting problems. Incorporating explicit tumor 3D information, such as tumor volume and surface area, enhances the grading model's performance and addresses the limitations of both approaches. By fusing information from multiple modalities, the model achieves a more precise and accurate characterization of tumors. The model I s trained and evaluated using two publicly available brain glioma datasets, achieving an AUC of 0.9684 on the validation set. The model's interpretability is enhanced through heatmaps, which highlight the tumor region. The proposed method holds promise for clinical application in tumor grading and contributes to the field of medical diagnostics for prediction.

Luminescence anisotropy and vorticity magnitude of a free turbulent jet

In the field of experimental fluid dynamics, the direct measurement of vorticity remains a challenge, even though it plays a crucial role in understanding turbulent flows. The present study explores the influence of the rotation of nanoparticles on their luminescence anisotropy as a potential novel measurement method. This relation opens a new field of flow diagnostics, based on the measurement of polarized intensity components. Potentially, the method allows for the direct measurement of the vorticity. For this, the canonical flow in this study is a turbulent round jet at ${{Re}} = {12\,000}$ and 14 400. It is confirmed that the flow regime has an influence on the luminescence anisotropy. Using a model of such deterministic rotations according to another work by the authors (Schmidt & Rösgen, Phys. Rev. Res., vol. 5, no. 3, 2023, 033006), the magnitude of the vorticity components is computed, since the presented set-up is limited to sensing the magnitude of these quantities. The computed components indicate the self-similarity of the vorticity magnitude. A large-eddy simulation is conducted for comparison with the experiments, demonstrating good agreement.

Therapeutic endoscopic ultrasound: an innovative technique, revolutionizing our practice

The field of digestive endoscopy evolves continuously, offering -patients significant advances both in the diagnostic and therapeutic fields. The introduction of lumen--apposing metal stents has enabled innovation in several endoscopic techniques, including endoscopic ultrasound--guided gallbladder drainage, choledochoduodeno-stomy, gastroenteroanastomosis, and transgastric endoscopic retrograde cholangiopancreatography (EDGE). Compared to traditional treatment methods, these procedures have shown excellent success rates, coupled with a reduced risk of postoperative morbidity and lower costs.

Recognition of mixed-sequence double-stranded DNA regions using chimeric Invader/LNA probes.

Development of robust oligonucleotide-based probe technologies, capable of recognizing specific regions of double-stranded DNA (dsDNA) targets, continues to attract considerable attention due to the promise of tools for modulation of gene expression, diagnostic agents, and new modalities against genetic diseases. Our laboratory pursues the development of various strand-invading probes. These include Invader probes, i.e., double-stranded oligonucleotide probes with one or more +1 interstrand zipper arrangements of intercalator-functionalized nucleotides like 2'-O-(pyren-1-yl)methyl-RNA monomers, and chimeric Invader/γPNA probes, i.e., heteroduplex probes between individual Invader strands and complementary γPNA strands. Here we report on the biophysical properties and dsDNA-recognition characteristics of a new class of chimeric probes-chimeric Invader/LNA probes-which are comprised of densely modified Invader strands and fully modified complementary LNA strands. The chimeric Invader/LNA probes form labile and distorted heteroduplexes, due to an apparent incompatibility between intercalating pyrene moieties and LNA strands. In contrast, the individual Invader and LNA strands form very stable duplexes with complementary DNA, which provides the driving force for near-stoichiometric recognition of model double-stranded DNA targets with single base-pair accuracy. The distinctive properties of chimeric Invader/LNA probes unlock exciting possibilities in molecular biology, and diagnostic and therapeutic fields.

Gastrointestinal PCR panel results and antibiotic use in acute gastroenteritis cases: How appropriate are we in our usage?

BackgroundWe aimed to determine the pathogens detected by the Gastrointestinal (GI) PCR panel in patients with acute gastroenteritis (AGE), the evaluation of antibiotic use in these patients, and the investigation of the role of laboratory parameters in differentiating viral and bacterial etiologies. MethodsThe demographic characteristics, GI PCR panel results, laboratory investigations, antibiotic usage, and appropriateness of antibiotic treatment were investigated in AGE patients. ResultsA total of 175 adult patients with AGE and GI PCR panel results were included in the study. The most common pathogens were EPEC (24.6%) and C. difficile (18.3%). Among the 102 patients receiving antibiotic treatment, 34.3% were evaluated as inappropriate antibiotic use. WBC, CRP, procalcitonin, CRP/albumin ratio, and procalcitonin/albumin ratio were found to be significantly higher in cases with bacterial origin. ConclusionsThe utilization of GI PCR panels in AGE patients has revolutionized the field of diagnostics by providing rapid and accurate identification of pathogens. In units without the possibility of GI PCR testing, CRP, procalcitonin, CRP/albumin ratio and procalcitonin/albumin ratio may be useful in the decision of antibiotic treatment.

Application of quantum computing in image processing for recognition of infectious diseases of wheat

This study is devoted to the development and application of quantum methods in the field of diagnostics of infectious diseases of wheat. Taking into account the relevance of the problem of agriculture and the need to improve the efficiency of plant disease control, the work proposes a new approach based on the combined use of quantum computing, image processing and machine learning. Quantum image processing techniques have been applied to improve contrast, filter noise, and analyze key features of infectious diseases in the early stages of their development. The developed quantum machine learning models demonstrate high ac-curacy in image classification, which contributes to earlier and more accurate detection of diseases. The study results highlight the effectiveness of quantum methods in agriculture and provide new tools for more accurate diagnosis of infectious plant diseases. The prospects for introducing this approach into agriculture mean the possibility of improving yields, reducing the use of chemicals and ensuring food security.

Применение нейронных сетей для диагностики устройств контактной сети: современные подходы и перспективы

The article discusses the prospects of using neural networks for information processing in the field of diagnostics of contact network devices. An overview of software and modern methods using neural networks has been presented, an analysis of software complexes based on fundamentally new methods of data processing obtained during the diagnosis of a contact network has been carried out. For further research, promising software solutions used for analyzing photo and video files have been noted: OpenCV, TensorFlow Object Detection API, YOLO, Amazon Rekognition Video и IBM Watson Visual Recognition.

Interdisciplinary collaboration in the diagnostic practice of the Integrated Youth Care in Flanders: A focus group study

Background: In 2020, the Flemish Centre of Excellence in Diagnostics (Kwaliteitscentrum voor Diagnostiek vzw) published the General Intersectoral Guidelines for Diagnostics (GIGD). The goal of the GIGD is to aid professionals working in different (mental) health care sectors in Flanders to implement high-quality diagnostic processes. The GIGD defines high-quality diagnostic processes by naming and explaining seven important practices. It is unclear, however, how the GIGD impacted the diagnostic field since its publication and to what extent the practices are implemented. Therefore, this study examined how one of those practices, namely interdisciplinary collaboration, is used in the Integrated Youth Care in Flanders and what the needs are to strengthen this practice further. 
 Methods: Focus groups were organized with professionals in diagnostics working in nine organisations of the Integrated Youth Care in Flanders, among which centers of mental health care, rehabilitation, developmental disability, student guidance, pediatric psychiatry, etc. The number of participants of each organisation ranged from 1 to 15, with no participants from the centers of pediatric psychiatry. In total, 65 professionals participated. In each focus group, an introduction in the GIGD was followed by a structured discussion about the way in which diagnostic processes are carried out in each organisation and how interdisciplinary collaboration is present and which difficulties are met during the process. 
 Results: Participants from all organisations agree that interdisciplinary collaboration is at the heart of good diagnostic trajectories within their own organisation. Important features concern the inclusion of multiple and diverse viewpoints in an interdisciplinary team with members from different backgrounds and levels of experience; a trusting atmosphere to discuss and promote different opinions; time and resources to allow an in-depth discussion; an (external) supervisor to moderate and guide group processes. Participants further highlight the importance of continuous and joint care across organisations in Child- and Youth care. However, several pitfalls were addressed, which seem hard to overcome, such as a lack of trust due to incomplete and erroneous knowledge about each other's professional operations, endless waiting lists thwarting appropriate continuation of care, and rigid policy requirements and restrictions. 
 Conclusion: All participating organisations understand the importance of interdisciplinary collaboration as a prerequisite for high-quality diagnostic processes and integrated care and long for more collaboration. However, several pitfalls and obstacles complicate matters. There is need for practical guidelines, information dissemination, workshops and intervisions, financial aid and more leeway in intersectoral endeavors to help professionals overcome these obstacles.

The organisation of the diagnostic field as part of the Policy Masterplan Early and Nearby: towards an integrated policy for welfare and healthcare for children, youth and families in Flanders, Belgium.

Introduction: The current organizational model in the field of Welfare, Public Health and Family in Flanders has reached its limits, resulting in severe accessibility problems, poor coordination between services, lack of balanced geographical spreading and suboptimal use of financial resources. As a first step, a concept note “Early and Nearby. Towards an integrated policy for children, youth, and families.” was drafted by the Flemish authorities. A masterplan was then developed in a participatory manner by four strategic circles and two consultation groups on specific themes. The aim of the strategic circle on diagnostic activities was to develop an alternative patient-centred organizational model, ensuring diagnostic activities as near and early as possible. Methods: A strategic circle was formed with stakeholders from all institutions offering diagnostic evaluations for children and adolescents in Flanders, patient associations representatives and representatives of the relevant policy departments. Participants had a high level of expertise in and knowledge of the organization and/or policy of diagnostic evaluations. Focus groups were organised per theme. Data was analysed iteratively by the strategic circle coordinators (EC, KC, LH). A member check was organized every meeting. Results: 24 stakeholders (3 patient representatives, 6 policy representatives and 15 representatives from the providing and scientific field) participated. The proposed organizational model is based on insights on conceptual models such as whole networks, stepped care, integrated care and patient-centred care. A shared vision on the concept of diagnostic evaluations is needed. Diagnostic evaluations should be integrated in the child’s overall care trajectory. Starting points of the organizational model are (1) the central position of the child and its family, (2) interprofessional and interorganizational sensitization, knowledge and expertise sharing, (3) interorganizational coordination and collaboration in a shared responsibility for the child, (4) low-threshold provision of diagnostic evaluations on every level of expertise, in response of all needs, in every region, (5) goal-oriented diagnostic evaluations, usable in the child’s care trajectory, (6) no referral but scaling up of needed expertise and knowledge across organizational boundaries, (7) continuity throughout the diagnostic and care trajectory and (8) a shared quality framework. A regional distribution of knowledge and expertise, based on the populations’ needs, is required. At the local level, early detection and specialised diagnostic evaluations of common problems and disorders should be organized. At the sub-regional level, highly specialised evaluations of complex, atypical disorders and complex support needs should be organized. At the regional level, support for quality management should be provided to staff, organisations and networks, as well as support for the organisation and policies of the diagnostic field. Regulation, funding and quality control are governmental responsibilities. Conclusion: A patient-centred, network-based organisational model with integration of knowledge and expertise across organizational boundaries, with equal geographical distribution, and with shared responsibility for the children along the care and diagnostic trajectory is likely to improve accessibility and facilitate smooth trajectories. More research is needed on the framework conditions and implementation of the new organisational model, as well as a review of the current regulatory framework and funding principles of organisations.

MamoRef: an optical mammography device using whole-field CW diffuse reflectance. Presentation, validation and preliminary clinical results

Objective. MamoRef is an mammography device that uses near-infrared light, designed to provide clinically relevant information for the screening of diseases of the breast. Using low power continuous wave lasers and a high sensitivity CCD (Charge-coupled device) that captures a diffusely reflected image of the tissue, MamoRef results in a versatile diagnostic tool that aims to fulfill a complementary role in the diagnosis of breast cancer providing information about the relative hemoglobin concentrations as well as oxygen saturation. Approach. We present the design and development of an initial prototype of MamoRef. To ensure its effectiveness, we conducted validation tests on both the theoretical basis of the reconstruction algorithm and the hardware design. Furthermore, we initiated a clinical feasibility study involving patients diagnosed with breast disease, thus evaluating the practical application and potential benefits of MamoRef in a real-world setting. Main results. Our study demonstrates the effectiveness of the reconstruction algorithm in recovering relative concentration differences among various chromophores, as confirmed by Monte Carlo simulations. These simulations show that the recovered data correlates well with the ground truth, with SSIMs of 0.8 or more. Additionally, the phantom experiments validate the hardware implementation. The initial clinical findings exhibit highly promising outcomes regarding MamoRef’s ability to differentiate between lesions. Significance. MamoRef aims to be an advancement in the field of breast pathology screening and diagnostics, providing complementary information to standard diagnostic techniques. One of its main advantages is the ability of determining oxy/deoxyhemoglobin concentrations and oxygen saturation; this constitutes valuable complementary information to standard diagnostic techniques. Besides, MamoRef is a portable and relatively inexpensive device, intended to be not only used in specific medical imaging facilities. Finally, its use does not require external compression of the breast. The findings of this study underscore the potential of MamoRef in fulfilling this crucial role.

Singlet oxygen-based photoelectrochemical detection of single-point mutations in the KRAS oncogene

Single nucleotide point mutations in the KRAS oncogene occur frequently in human cancers, rendering them intriguing targets for diagnosis, early detection and personalized treatment. Current detection methods are based on polymerase chain reaction, sometimes combined with next-generation sequencing, which can be expensive, complex and have limited availability. Here, we propose a novel singlet oxygen (1O2)-based photoelectrochemical detection methodology for single-point mutations, using KRAS mutations as a case study. This detection method combines the use of a sandwich assay, magnetic beads and robust chemical photosensitizers, that need only air and light to produce 1O2, to ensure high specificity and sensitivity. We demonstrate that hybridization of the sandwich hybrid at high temperatures enables discrimination between mutated and wild-type sequences with a detection rate of up to 93.9%. Additionally, the presence of background DNA sequences derived from human cell-line DNA, not containing the mutation of interest, did not result in a signal, highlighting the specificity of the methodology. A limit of detection as low as 112 pM (1.25 ng/mL) was achieved without employing any amplification techniques. The developed 1O2-based photoelectrochemical methodology exhibits unique features, including rapidity, ease of use, and affordability, highlighting its immense potential in the field of nucleic acid-based diagnostics.

(Invited) Manipulating Light Emission from Rare Earth Doped Nanoparticles for Applications in Theranostics

Luminescent nanomaterials that can be excited, as well as emit, in the near-infrared (NIR) have been investigated for use in a plethora of applications including nanomedicine, nanoelectronics, biosensing, bioimaging, photovoltaics, photocatalysis, etc. The use of NIR light for excitation mitigates some of the drawbacks associated with high-energy (UV or blue) excitation, for example, little to no background autofluorescence from the specimen under investigation as well as no incurred photodamage. Moreover, one of the biggest limitations is of course, that of penetration. As such, NIR light can penetrate tissues much better than high-energy light especially when these wavelengths lie within the three biological windows (BW-I: 700-950, BW-II: 1000-1350, BW-III: 1550-1870 nm) where tissues are optically transparent. At the forefront of NIR excited nanomaterials are rare earth doped nanoparticles, which due to their 4f electronic energy states can undergo conventional (Stokes) luminescence and emit in the three NIR biological windows. However, unlike other classes of nanoparticles, they can also undergo a multiphoton process (known as upconversion) where the NIR excitation light is converted to higher energies resulting in anti-Stokes luminescence spanning the UV-visible-NIR regions. Perhaps the biggest impact of such materials would be in the field of disease diagnostics and therapeutics, now commonly referred to as theranostics. Due to the versatility of their optical properties, it now becomes possible to generate high-energy light (UV or blue) in situ to trigger other light activated therapeutic modalities (i.e. drug release) while using the NIR emission for diagnostics (i.e. bioimaging, nanothermometry). Here, we present the synthesis of various NIR excited (and emitting) rare earth doped core/shell (and multishell) nanoparticles and demonstrate how their luminescence properties can be exploited for potential use in diverse biomedical applications.

Gamma radiation shielding by titanium alloy reinforced by polymeric composite materials

The Ti-6Al-4V alloy (TAV) has several desirable properties, including high density, strength, low corrosion, biocompatibility, and flexibility. Based on these attractive features, we study the gamma radiation shielding capabilities of a titanium alloy TAV strengthened by polymeric composite materials. Examining the TAV alloy demonstrates discernible X-ray diffraction (XRD) peaks corresponding to specific crystallographic planes, showing its crystalline nature. The produced composites exhibit mass attenuation coefficient (μm) values that are very competitive compared to those of other shielding materials recorded in the current literature. The study results provide compelling evidence that incorporating TAV into polymeric composites has considerable promise in their effectiveness as gamma radiation shielding materials. These favorable features can be attributable to a high strength-to-weight ratio, corrosion resistance, non-magnetic properties, and biocompatibility. This work describes the photon attenuation characteristics and performance of an innovative polymer composite constructed with a matrix reinforced with four different TAV content proportions (20, 30, 40, and 50 wt%). Composite materials significantly improve μm values, particularly as their density increases, especially at lower gamma energy levels. The attributes make composites highly suitable for utilization in the fields of radiation and diagnostics, where the presence of adequate shielding is of utmost importance. At the energy level of 662 keV, the μm of the shielding material exhibited a notable increase as the amount of TAV was gradually raised, reaching 0.075 at a loading rate of 20% and significantly improving to 0.136 at a loading rate of 50%. The study reveals that the half-value layer (HVL) of composites increases with the energy level of the incoming gamma photons, indicating that the composites can attenuate low-energy gamma radiation and that higher-energy photons require larger thicknesses. The HVL also depends on the amount of material filling the polymer matrix, and its effectiveness improves as filler material increases.