Targeting Vector Research Articles

ESOMA-DM1, a Maytansinoid-Based Theranostic Small-Molecule Drug Conjugate for Neuroendocrine Tumors.

Background: The main challenges of conventional chemotherapy lie in its lack of selectivity and specificity, leading to significant side effects. Using a small-molecule drug conjugate (SMDC) ensures specific delivery of a cytotoxic drug to the tumor site by coupling it to a targeting vector. This promising strategy can be applied to neuroendocrine tumors (NETs) by choosing a targeting vector that binds specifically to somatostatin receptor subtype 2 (SSTR2). Additionally, incorporation of a bifunctional chelate into the molecule enables complexation of both diagnostic and therapeutic radionuclides. Thus, it facilitates monitoring of the distribution of the SMDC in the body and allows for the implementation of combination therapy. In our study, we designed eSOMA-DM1, a SMDC combining the SSTR2-targeted octreotate peptide and the cytotoxic agent DM1 via a chelate-bridged linker (N3-Py-DOTAGA). This approach warrants conjugation of the targeting vector and the drug at opposite sites to avoid undesired steric hindrance effects. Methods: Synthesis of the DM1 moiety (4) involved a three-step synthetic route, followed by the conjugation to the cyclic peptide, N3-Py-DOTAGA-d-Phe-cyclo[Cys-Tyr-d-Trp-Lys-Thr-Cys]-Thr-OH, through a copper-free click reaction, resulting in eSOMA-DM1. Subsequent labeling with [111In]InCl3 gave a high radiochemical yield and purity. In vitro assessments of eSOMA-DM1 binding, uptake, and internalization were conducted in SSTR2-transfected U2OS cells. Ex vivo biodistribution and fluorescence imaging were performed in H69-tumor bearing mice. Results: eSOMA-DM1 exhibited an IC50 value for SSTR2 similar to the gold standard DOTA-TATE. The uptake of [111In]In-eSOMA-DM1 in U2OS.SSTR2 cells was 1.2-fold lower than that of [111In]In-DOTA-TATE. Tumor uptake in H69-xenografted mice was higher for [111In]In-eSOMA-DM1 at all-time points compared to [111In]In-DOTA-TATE. Prolonged blood circulation led to increased accumulation of [111In]In-eSOMA-DM1 in highly vascularized tissues, such as the lungs, skin, and heart. Excretion through the kidneys, liver, and spleen was also observed. Conclusion: eSOMA-DM1 is a SMDC developed for NET showing promising characteristics in vitro. However, the in vivo results obtained with [111In]In-eSOMA-DM1 suggest the need for adjustments to optimize its distribution.

Spleen Targeting Nucleic Acid Delivery Vector Based on Metal-Organic Frameworks.

Nucleic acids have attracted increasing attention as drugs due to their fascinating advantages, such as long-term efficacy and ease of preparation compared to proteins. The nucleic acid therapy relies heavily on delivery vectors, which can prevent the degradation of nucleic acids while assisting them in cellular internalization. However, commonly used nonviral vector liposomes easily accumulate in the liver, which can limit their application in extrahepatic diseases. Herein, a potential spleen targeting vector for nucleic acids is developed based on the metal-organic frameworks. The plasmids are encapsulated inside the nanoscale zeolitic imidazolate framework (ZIF) via coprecipitation. The co-encapsulation of the cationic polymer poly(ether imide) (PEI) and the stabilizer polyvinylpyrrolidone (PVP) can significantly improve particle dispersion and stability. The prepared nanoparticles allow efficient transfection in vitro, mainly through clathrin-mediated and caveolae-mediated endocytosis. The biodistribution in mice shows that 46% of the nanoparticles accumulate in the spleen, which is much higher than that of the liposomes. The vector can successfully deliver plasmids to extrahepatic organs for protein synthesis and even induce an immune response. The elaborate ZIF-based nanoparticle may offer a new route for extrahepatic, especially spleen targeting delivery for the nucleic acids.

Prodrug Nanomedicine for Synovium Targeted Therapy of Inflammatory Arthritis: Insights from Animal Model and Human Synovial Joint Fluid.

Many patients cannot tolerate low-dose weekly methotrexate (MTX) therapy for inflammatory arthritis treatment due to life-threatening toxicity. Although biologics offer a target-specific therapy, it raises the risk of serious infections and even cancer due to immune system suppression. We introduce an anti-inflammatory arthritis MTX ester prodrug using a long-circulating biocompatible polymeric macromolecule: folic acid (FA) functionalized hyperbranched polyglycerol (HPG). In vitro the drug MTX is incrementally released through pH and enzymatic degradation over 2 weeks. The role of matrix metalloproteinases (MMPs) in site-specific prodrug activation was verified using synovial fluid (SF) of 26 rheumatology patients and 4 healthy controls. Elevated levels of specific MMPs-markers of joint inflammation-positively correlated with enhanced prodrug release explained by acid-catalyzed hydrolysis of esters by proteases. Intravenously administered 111In-radiolabeled prodrug confirmed by SPECT/CT imaging that it accumulated preferentially in inflamed joints while reducing off-target side-effects in a mouse model of rheumatoid arthritis (RA). Added FA as a targeting vector prolonged prodrug action; prodrug with 4x less MTX applied every 2 weeks was as effective as weekly MTX therapy. The preclinical results suggest a prodrug-based strategy for the treatment of inflammatory joint diseases, with potential for other chronic inflammatory diseases and cancer.

Empirical best predictors under multivariate Fay-Herriot models and their numerical approximation

Small area estimation of multivariable non-linear domain indicators using aggregated data is addressed. By assuming that the target vector follows a multivariate Fay-Herriot model, empirical best predictors of domain parameters that are arbitrary Lebesgue-measurable functions of multiple target variables are derived. In this context, Monte Carlo and Gauss-Hermite quadrature methods for integral approximation are discussed. A parametric bootstrap algorithm for mean squared error estimation is presented. Simulation experiments are conducted to study the behaviour of the introduced methodology. Moreover, an illustrative application to real data from the Spanish labour force survey is provided. In this example, province-level unemployment rates, crossed by age classes and sex, are estimated.

Optimizing Distributions for Associated Entropic Vectors via Generative Convolutional Neural Networks.

The complete characterization of the almost-entropic region yields rate regions for network coding problems. However, this characterization is difficult and open. In this paper, we propose a novel algorithm to determine whether an arbitrary vector in the entropy space is entropic or not, by parameterizing and generating probability mass functions by neural networks. Given a target vector, the algorithm minimizes the normalized distance between the target vector and the generated entropic vector by training the neural network. The algorithm reveals the entropic nature of the target vector, and obtains the underlying distribution, accordingly. The proposed algorithm was further implemented with convolutional neural networks, which naturally fit the structure of joint probability mass functions, and accelerate the algorithm with GPUs. Empirical results demonstrate improved normalized distances and convergence performances compared with prior works. We also conducted optimizations of the Ingleton score and Ingleton violation index, where a new lower bound of the Ingleton violation index was obtained. An inner bound of the almost-entropic region with four random variables was constructed with the proposed method, presenting the current best inner bound measured by the volume ratio. The potential of a computer-aided approach to construct achievable schemes for network coding problems using the proposed method is discussed.

Lead-212/Bismuth-212 InVivo Generator Based on Ultrasmall Silver Telluride Nanoparticles.

Radionuclide therapy employing alpha emitters holds great potential for personalized cancer treatment. However, certain challenges remain when designing alpha radiopharmaceuticals, including the lack of stability of used radioconjugates due to nuclear decay events. In this work, ultrasmall silver telluride nanoparticles with a core diameter of 2.1 nm were prepared and radiolabeled with lead-212 using a chelator-free method with a radiolabeling efficiency of 75%. The results from the invitro radiochemical stability assay indicated a very high retention of bismuth-212 despite the internal conversion effects originating from the decay of 212Pb. To further evaluate the potential of the nanoparticles, they were radiolabeled with indium-111, and their cell uptake and subcellular distribution were determined in 2D U87 cells, showing accumulation in the nucleus. Although not intentional, it was observed that the indium-111-radiolabeled nanoparticles induced efficient tumor cell killing, which was attributed to the Auger electrons emitted by indium-111. Combining the results obtained in this work with other favorable properties such as fast renal clearance and the possibility to attach targeting vectors on the surface of the nanoparticles, all well-known from the literature, these ultra-small silver telluride nanoparticles provide exciting opportunities for the design of theragnostic radiopharmaceuticals.

Multimodal interactions in Stomoxys navigation reveal synergy between olfaction and vision

Stomoxys flies exhibit an attraction toward objects that offer no rewards, such as traps and targets devoid of blood or nectar incentives. This behavior provides an opportunity to develop effective tools for vector control and monitoring. However, for these systems to be sustainable and eco-friendly, the visual cues used must be specific to target vector(s). In this study, we modified the existing blue Vavoua trap, which was originally designed to attract biting flies, to create a deceptive host attraction system specifically biased toward attracting Stomoxys. Our research revealed that Stomoxys flies are attracted to various colors, with red proving to be the most attractive and selective color for Stomoxys compared to the other colors tested. Interestingly, our investigation of the cattle–Stomoxys interaction demonstrated that Stomoxys flies do not prefer a specific livestock fur color phenotype, despite variation in the spectrum. To create a realistic sensory impression of the trap in the Stomoxys nervous system, we incorporated olfactory cues from livestock host odors that significantly increased trap catches. The optimized novel polymer bead dispenser is capable of effectively releasing the attractive odor carvone + p-cresol, with strong plume strands and longevity. Overall, red trap baited with polymer bead dispenser is environmentally preferred.

Creation of an in vitro model of GM1 gangliosidosis by CRISPR/Cas9 knocking-out the GLB1 gene in SH-SY5Y human neuronal cell line.

GM1 gangliosidosis is one type of hereditary error of metabolism that occurs due to the absence or reduction of β-galactosidase enzyme content in the lysosome of cells, including neurons. In vitro, the use of neural cell lines could facilitate the study of this disease. By creating a cell model of GM1 gangliosidosis on the SH-SY5Y human nerve cell line, it is possible to understand the main role of this enzyme in breaking down lipid substrate and other pathophysiologic phenomena this disease. To knock-out the human GLB1 gene, guides targeting exons 14 and 16 of the GLB1 gene were designed using the CRISPOR and CHOP-CHOP websites, and high-efficiency guides were selected for cloning in the PX458 vector. After confirming the cloning, the vectors were transformed into DH5α bacteria and then the target vector was extracted and transfected into human nerve cells (SH-SY5Y cell line) by electroporation. After 48 h, GFP+ cells were sorted using the FACS technique and homozygous (compound heterozygous) single cells were isolated using the serial dilution method and sequencing was done to confirm them. Finally, gap PCR tests, X-gal and Periodic acid-Schiff (PAS) staining, and qPCR were used to confirm the knock-out of the human GLB1 gene. Additionally, RNA sequencing data analysis from existing data of the Gene Expression Omnibus (GEO) was used to find the correlation of GLB1 with other genes, and then the top correlated genes were tested for further evaluation of knock-out effects. The nonviral introduction of two guides targeting exons 14 and 16 of the GLB1 gene into SH-SY5Y cells led to the deletion of a large fragment with a size of 4.62 kb. In contrast to the non-transfected cell, X-gal staining resulted in no blue color in GLB1 gene knock-out cells indicating the absence of β-galactosidase enzyme activity in these cells. Real-time PCR (qPCR) results confirmed the RNA-Seq analysis outcomes on the GEO data set and following the GLB1 gene knock-out, the expression of its downstream genes, NEU1 and CTSA, has been decreased. It has been also shown that the downregulation of GLB1-NEU1-CTSA complex gene was involved in suppressed proliferation and invasion ability of knock-out cells. This study proved that using dual guide RNA can be used as a simple and efficient tool for targeting the GLB1 gene in nerve cells and the knockout SH-SY5Y cells can be used as a model investigation of basic and therapeutic surveys for GM1 gangliosidosis disease.

Targeted Radionuclide Therapy in Glioblastoma.

Despite the development of various novel therapies, glioblastoma (GBM) remains a devastating disease, with a median survival of less than 15 months. Recently, targeted radionuclide therapy has shown significant progress in treating solid tumors, with the approval of Lutathera for neuroendocrine tumors and Pluvicto for prostate cancer by the US Food and Drug Administration (FDA) and the European Medicines Agency (EMA). This achievement has shed light on the potential of targeted radionuclide therapy for other solid tumors, including GBM. This review presents the current status of targeted radionuclide therapy in GBM, highlighting the commonly used therapeutic radionuclides emitting alpha, beta particles, and Auger electrons that could induce potent molecular and cellular damage to treat GBM. We then explore a range of targeting vectors, including small molecules, peptides, and antibodies, which selectively target antigen-expressing tumor cells with minimal or no binding to healthy tissues. Considering that radiopharmaceuticals for GBM are often administered locoregionally to bypass the blood-brain barrier (BBB), we review prominent delivery methods such as convection-enhanced delivery, local implantation, and stereotactic injections. Finally, we address the challenges of this therapeutic approach for GBM and propose potential solutions.

Complexation of 3p-C-NETA with radiometal ions: A density functional theory study for targeted radioimmunotherapy

Bifunctional chelators (BFCs) are vital in the design of effective radiopharmaceuticals, as they are able to bind to both a radiometal ion and a targeting vector. The 3p-C-NETA or 4-[2-(bis-carboxy-methylamino)-5-(4-nitrophenyl)-entyl])-7-carboxymethyl-[1,4,7]tri-azonan-1-yl acetic acid is a novel and promising BFC, developed for diagnostic and therapeutic purposes. The binding affinity between the BFC and radiometal ion significantly impacts their effectiveness. Predicting the equilibrium constants for the formation of 1:1 radiometals/chelator complexes (log K1 values) is crucial for designing BFCs with improved affinity and selectivity for radiometals. The purpose of this study is to evaluate the complexation of Ga3+, Tb3+, Bi3+, and Ac3+ radiometal ions with 3p-C-NETA using density functional theory (B3LYP and M06-HF functional) and 6-311G(d)/SDD basis sets, where the 1,4,7,10-tetrazacyclodecane-1,4,7,10-tetracetic acid (DOTA) was employed as a benchmark. Formation of the [Ac3+(3p-C-NETA)(H2O)]- complexes is predicted to be markedly less stable compared to the other complexes, exhibiting the lowest chemical hardness and the highest chemical softness. Additionally, the chelation stability of the complexes is mainly determined by ligand-ion and ion-water interactions, which depend on the atomic charge and atomic radius of the metal ion.

STTraj2Vec: A spatio-temporal trajectory representation learning approach

Computing trajectory similarity plays a critical role in various spatio-temporal applications that involve trajectory analysis. In recent years, trajectory representation learning has been extensively studied and applied for trajectory similarity calculation. However the majority of existing algorithms for trajectory representation generally have two problems. The first problem is the emphasis of spatial similarity over temporal similarity, and even to discard the temporal dimension of spatio-temporal trajectories. As a result, the outputs of these approaches cannot fully represent the similarity of spatio-temporal trajectories. The second problem is the introduction of additional information, such as the topology of the road network, which increases the uncertainty of capturing the spatio-temporal correlation of trajectories and prevents their application in scenarios where it is difficult to obtain such information. This poses a significant challenge when dealing with complex and time-varying traffic networks. This paper proposes a novel method, named STTraj2Vec (Spatio-temporal Trajectory 2 Vector), which relies only on spatio-temporal trajectories to capture their similarity without spatio-temporal separation. This takes into account the whole spatio-temporal trajectory information. In this method, an extended clustering algorithm is introduced, which maps the trajectory into a point-region quadtree, and constructs a time-varying virtual network structure based on the point-region quadtree. In this method, an extended clustering algorithm is introduced, which maps each trajectory into a point-region quadtree, and then completes density clustering through the adjacency relation of leaf nodes to construct a time-varying virtual network structure. This virtual network structure not only considers the spatial proximity, but also the time, so as to reflect the spatio-temporal characteristics of the trajectory more accurately. Then, a novel spatially and temporally integrated random walk algorithm is designed, which carries out spatiotemporal random walk on the virtual network structure, to capture the spatiotemporal characteristics of the trajectory, and thus obtains the representation of all nodes in the virtual network. Furthermore, each trajectory is converted into a sequence of vectors on the virtual road network according to the latitude, longitude, and time of the trajectory points. Finally, based on these node representations and trajectories, a transformer model with ranking loss is employed to capture the distinct contributions of the various locations and times to the similarity computation and encode each sequence of vectors into target vectors. Experiments on two public datasets show that STTraj2Vec is superior to the state-of-the-art methods in terms of effectiveness for top-k trajectory similarity search and trajectory clustering, while exhibiting low parameter sensitivity and high model robustness.

Cytokine-induced killer cells-mediated chlorin e6-loaded gold nanostars for targeted NIR imaging and immuno-photodynamic combination therapy for lung cancer

Recently, cytokine-induced killer (CIK) cells have a broad application prospect in the comprehensive diagnosis and treatment of tumors owing to their unique characteristics of killing and targeting malignant tumors. Herein, we report a facile strategy for synthesis of monodisperse gold nanostars (GNSs) based on PEGylation and co-loaded with the photosensitizer chlorin e6 (Ce6) to form GNSs-PEG@Ce6 NPs. Then employing CIK cells loading the as-prepared GNSs-PEG@Ce6 NPs to fabricate a CIK cells-based drug delivery system (GNSs-PEG@Ce6-CIK) for lung cancer. Among them, GNSs was functioned as transport media, Ce6 acted as the near-infrared (NIR) fluorescence imaging agent and photodynamic therapy (PDT), and CIK cells served as targeting vectors for immunotherapy, which can increase the efficiency of tumor enrichment and treatment effect. The results of cellular experiments demonstrated that GNSs-PEG@Ce6 NPs had good dispersibility, water solubility and low toxicity under physiological conditions, and the cultured CIK cells had strong anti-tumor properties. Subsequently, GNSs-PEG@Ce6-CIK could effectively inhibit the growth of A549 cells under the exposure of 633 nm laser, which showed stronger killing effect than that of GNSs-PEG@Ce6 NPs or CIK cells. In addition, they showed good tumor targeting and tumor synergistic killing activity in vivo. Therefore, GNSs-PEG@Ce6-CIK was constructed for targeted NIR fluorescence imaging, enhanced PDT and immunotherapy of lung cancer.

Robust Bayesian target vector optimization for multi-stage manufacturing processes

This research focuses on optimizing multi-stage manufacturing processes using Bayesian optimization (BO) with a robust Expected Improvement (EI) acquisition function. The aim is to optimize towards pre-selected target vectors, not to just minimize or maximize a function. To achieve this, we minimize the Euclidean distance between the actual and target output vectors, which requires transforming the Gaussian surrogate model posterior distribution into a non-central χ2(NCχ2) distribution. Furthermore, the distance measure additionally uses aleatoric uncertainty estimates of the actual output vectors to achieve robustness. We use a cascaded method that also considers the optimization results of intermediate stages, whereby optimization results are propagated from the last stage towards the first stage in each optimization iteration. By considering intermediate process outputs and aleatoric effects, our approach provides a robust optimization method for multi-stage manufacturing processes. To validate our method and to evaluate its properties, we use two artificial use cases. Moreover, we evaluate our approach in an industrial multi-stage forging process for the manufacturing of a nickel basis superalloy turbine disk, where involved stages are represented by corresponding 2D finite element method (FEM) DEFORM simulations. Evaluation suggests that our approach is superior in optimizing multi-stage manufacturing processes by considering all stage outcomes, robust distance measures, and the use of appropriate uncertainty distributions.

A Review of Advances in Molecular Imaging of Rheumatoid Arthritis: From In Vitro to Clinic Applications Using Radiolabeled Targeting Vectors with Technetium-99m.

Rheumatoid arthritis (RA) is a systemic autoimmune disorder caused by inflammation of cartilaginous diarthrodial joints that destroys joints and cartilage, resulting in synovitis and pannus formation. Timely detection and effective management of RA are pivotal for mitigating inflammatory arthritis consequences, potentially influencing disease progression. Nuclear medicine using radiolabeled targeted vectors presents a promising avenue for RA diagnosis and response to treatment assessment. Radiopharmaceutical such as technetium-99m (99mTc), combined with single photon emission computed tomography (SPECT) combined with CT (SPECT/CT), introduces a more refined diagnostic approach, enhancing accuracy through precise anatomical localization, representing a notable advancement in hybrid molecular imaging for RA evaluation. This comprehensive review discusses existing research, encompassing in vitro, in vivo, and clinical studies to explore the application of 99mTc radiolabeled targeting vectors with SPECT imaging for RA diagnosis. The purpose of this review is to highlight the potential of this strategy to enhance patient outcomes by improving the early detection and management of RA.

Mechanistic Characterization of Cancer-associated Fibroblast Depletion via an Antibody-Drug Conjugate Targeting Fibroblast Activation Protein.

The direct elimination of FAP-expressing CAFs disrupts the cross-talk with cancer cells leading to a proinflammatory response and alterations in the immune microenvironment and antitumor immune response.

Receptor-Targeted Peptide Conjugates Based on Diphosphines Enable Preparation of 99mTc and 188Re Theranostic Agents for Prostate Cancer.

Benchtop 99Mo/99mTc and 188W/188Re generators enable economical production of molecular theranostic 99mTc and 188Re radiopharmaceuticals, provided that simple, kit-based chemistry exists to radiolabel targeting vectors with these radionuclides. We have previously described a diphosphine platform that efficiently incorporates 99mTc into receptor-targeted peptides. Here, we report its application to label a prostate-specific membrane antigen (PSMA)-targeted peptide with 99mTc and 188Re for diagnostic imaging and systemic radiotherapy of prostate cancer. Methods: Two diphosphine-dipeptide bioconjugates, DP1-PSMAt and DP2-PSMAt, were formulated into kits for radiolabeling with 99mTc and 188Re. The resulting radiotracers were studied invitro, in prostate cancer cells, and invivo in mouse xenograft models, to assess similarity of uptake and biodistribution for each 99mTc/188Re pair of agents. Results: Both DP1-PSMAt and DP2-PSMAt could be efficiently radiolabeled with 99mTc and 188Re using kit-based methods to furnish the isostructural compounds M-DP1-PSMAt and M-DP2-PSMAt (M = [99mTc]Tc, [188Re]Re). All 99mTc/188Re radiotracers demonstrated specific uptake in PSMA-expressing prostate cancer cells, with negligible uptake in prostate cancer cells that did not express PSMA or in which PSMA uptake was blocked. M-DP1-PSMAt and M-DP2-PSMAt also exhibited high tumor uptake (18-30 percentage injected dose per gram at 2 h after injection), low retention in nontarget organs, fast blood clearance, and excretion predominantly via a renal pathway. Importantly, each pair of 99mTc/188Re radiotracers showed near-identical biologic behavior in these experiments. Conclusion: We have prepared and developed novel pairs of isostructural PSMA-targeting 99mTc/188Re theranostic agents. These generator-based theranostic agents have potential to provide access to the benefits of PSMA-targeted diagnostic imaging and systemic radiotherapy in health care settings that do not routinely have access to either reactor-produced 177Lu radiopharmaceuticals or PET/CT infrastructure.

FDS-MOMEDA: optimization-blind deconvolution in finite high-dimensional spaces for extracting pulse signal in rolling bearing fault diagnosis

Rolling bearing fault diagnosis is crucial for ensuring the safe and reliable operation of mechanical equipment. Detecting faults directly from measurement signals is challenging due to severe noise and interference. Blind deconvolution (BD), as a preferred method, effectively recovers periodic pulses from the measured vibration signals of faulty bearings. This study introduces a simulated annealing-based BD approach to enhance the pulse signal components reflecting faults in vibration signals measured on rolling bearings. This method iteratively searches for the optimal coordinates in a high-dimensional orthogonal optimization space, where the optimal coordinates reflect the combination of the inverse filter coefficients. Compared to the generalized spherical optimization space used in the ‘Optimization-Blind Deconvolution’ method in previous works, the proposed finite high-dimensional optimization space helps overcome the problem of inverse filter coefficient convergence, allowing for the design of inverse filters without limit of its shape. To better accommodate the cyclostationarity characteristics of bearing signal measured in reality, the proposed method employs a target vector that allows for uncertainty in pulse occurrence instants, thus overcomes challenges introduced by pseudo-periodic phenomena resulting from bearing slippage. Numerical simulations and experimental results on real bearing vibration signals confirm that the proposed method can design more flexible filters to enhance pulse-like patterns in signals, effectively utilize limited filter resources. Its capacity to tolerate inaccurate fault period estimates, high background noise, and pulse randomness enables it to effectively address vibration measurement signals in real-world scenarios.

ETFC-01: a dual-labeled chelate-bridged tracer for SSTR2-positive tumors.

Integrating radioactive and optical imaging techniques can facilitate the prognosis and surgical guidance for cancer patients. Using a single dual-labeled tracer ensures consistency in both imaging modalities. However, developing such molecule is challenging due to the need to preserve the biochemical properties of the tracer while introducing bulky labeling moieties. In our study, we designed a trifunctional chelate that facilitates the coupling of the targeting vector and fluorescent dye at opposite sites to avoid undesired steric hindrance effects. The synthesis of the trifunctional chelate N3-Py-DOTAGA-(tBu)3 (7) involved a five-step synthetic route, followed by conjugation to the linear peptidyl-resin 8 through solid-phase synthesis. After deprotection and cyclization, the near-infrared fluorescent dye sulfo-Cy.5 was introduced using copper free click chemistry, resulting in eTFC-01. Subsequently, eTFC-01 was labeled with [111In]InCl3. In vitro assessments of eTFC-01 binding, uptake, and internalization were conducted in SSTR2-transfected U2OS cells. Ex-vivo biodistribution and fluorescence imaging were performed in H69-tumor bearing mice. eTFC-01 demonstrated a two-fold higher IC50 value for SSTR2 compared to the gold standard DOTA-TATE. Labeling of eTFC-01 with [111In]InCl3 gave a high radiochemical yield and purity. The uptake of [111In]In-eTFC-01 in U2OS.SSTR2 cells was two-fold lower than the uptake of [111In]In-DOTA-TATE, consistent with the binding affinity. Tumor uptake in H69-xenografted mice was lower for [111In]In-eTFC-01 at all-time points compared to [111In]In-DOTA-TATE. Prolonged blood circulation led to increased accumulation of [111In]In-eTFC-01 in highly vascularized tissues, such as lungs, skin, and heart. Fluorescence measurements in different organs correlated with the radioactive signal distribution. The successful synthesis and coupling of the trifunctional chelate to the peptide and fluorescent dye support the potential of this synthetic approach to generate dual labeled tracers. While promising in vitro, the in vivo results obtained with [111In]In-eTFC-01 suggest the need for adjustments to enhance tracer distribution.

Noninvasive focused ultrasound-mediated delivery of rAAV9-EGFP vectors for neuronal targeting in rats

ObjectiveTo evaluate the synergistic potential of Focused Ultrasound (FUS) in conjunction with microbubbles (MB) and recombinant adeno-associated virus serotype 9 (rAAV9) vectors for targeted gene delivery to neuronal cells in rats, optimizing gene expression conditions and assessing any adverse effects. MethodsThe parameters for permeability enhancement of the rat's blood-brain barrier (BBB) were established using FUS+MB, with MRI scans and Evans Blue (EB) dye assisting in the evaluation. Rats underwent FUS-mediated transfection using rAAV9-Syn-EGFP vectors produced via a triple-transfection in HEK293T cells. Following this, the uptake and expression of GFP in targeted brain regions were evaluated using confocal fluorescence microscopy at various time intervals. Inflammatory responses post-FUS treatment were tracked by observing levels of GFAP, a marker for astrocytic activation, and TNF-α, a pro-inflammatory cytokine. Motor behavior effects post-intervention were gauged using the Rotarod test across multiple groups over a span of four weeks. ResultsFUS+MB affected BBB permeability, with optimal results at 4 W for 200 s showing 85 % permeability and evident Gd-DTPA leakage. Settings beyond these resulted in tissue damage. Control groups exhibited a basal GFP expression of 2 % ± 0.5 %, whereas FUS+MB with rAAV-EGFP injections substantially increased GFP expression to about 67 % ± 6 % in targeted neurons. This GFP expression peaked at three weeks post-treatment and remained evident six months later. Following FUS treatment, both GFAP and TNF-α levels underwent fluctuations before eventually nearing their baseline values. The Rotarod test revealed no significant behavioral differences post-treatments among the groups. ConclusionsCombining FUS+MB with rAAV offers an innovative approach to enhance therapeutic delivery to the central nervous system (CNS) by transiently adjusting BBB permeability.

Molecular approaches to deploy singlet oxygen in a Leishmania model as an unassailable biocide for disease mitigation and vector control

Singlet oxygen (1O2) is a potent biocide potentially deployable for integrated control of tropical diseases and their insect vectors. This very short-lived free radical is highly destructive of cellular molecules when generated intracellularly. Most organisms, including parasites and vectors, are defenseless against 1O2 except for plants, which produce it abundantly during photosynthesis, hence, the acquisition of specific mechanisms for its detoxification. In the presence of O2 under physiological conditions, certain dyes or photosensitizers (PS), e.g., porphyrins and phthalocyanines (PC), are excitable by light to produce biocidal 1O2. Its half-life is in the order of microseconds, necessitating its intracellular generation in order to harness its biocidal activity most effectively. This is achievable by loading cells with PS for excitation with light to produce 1O2in situ. One example to achieve this is the genetic engineering of Leishmania to complement its inherent defects in porphyrin biosynthesis, resulting in cytosolic accumulation of abundant PS in the form of uroporphyrin 1 (URO). Another example is the chemical engineering of PC for hydrophilicity, thereby facilitating the endocytosis of such PS by cells. Leishmania loaded with cytosolic URO and endosomal PC are inactivated by the 1O2 produced via light-activation of these PS in the two different cell compartments. The inactivated Leishmania are nonviable, but have their natural vaccines and adjuvants well-preserved for prophylactic vaccination against experimental leishmaniasis. 1O2-inactivated Leishmania is potentially useful to serve as a platform for the safe and effective delivery of transgenically add-on vaccines against malignant and viral diseases in experimental models. Hydrophilic and cationic PC were also shown experimentally to act as a new type of dim light-activable insecticides, i.e., their mosquito larvicidal activities with <µM LD50 values. Similar results are expected by studying PC in additional laboratory insect models. A significant advantage has long been attributed to this type of insecticide, i.e., their aversion to a selection of genetic variants for resistance. An additional advantage of PC is their excitability to produce insecticidal 1O2 with deep-penetrating red or infrared light invisible to most insects, thereby potentially increasing the range and scope of targetable insect vectors.