The highly selective permeability of the human blood-brain barrier presents a major obstacle to neurological disease modeling. Established 2D cell cultures and animal models are unable to accurately reproduce the physiological and molecular features of the human blood-brain barrier, limiting the translation of bench to bedside. Recent advances in the use of human induced pluripotent stem cells and organoid engineering have enabled the development of more physiologically relevant in vitro brain models for studying blood-brain barrier function. Blood-brain barrier organoids, mimic key structural and functional features of the blood-brain barrier. Moreover, integration of blood brain barrier organoids with brain organoids or microphysiological systems allows the formation of functional neurovascular units that better represent in vivo conditions. The development of scalable, reproducible, and partially vascularized blood-brain barrier organoid models holds promise for high-throughput drug discovery platforms, and the development of personalized therapeutic strategies for central nervous system disorders.

Despite the revolutionized diagnostic effect of fluorine-18 -fludeoxyglucose ([18F]-FDG) as a positron emission tomography (PET) radiotracer in oncological divisions, lack of specificity and sensitivity in discovery of some tumor subtypes was inevitable. Fibroblast activation protein (FAP) is overexpressed in a vast majority of neoplasms, particularly in more than 90% of epithelial tumors which could be an appropriate target for evaluation of tumor’s molecular and metabolic functions by FAP inhibitor (FAPI) ligands. Considerably extensive radiolabeled FAPIs have been investigated during clinical trials for diagnostic as well as theranostic applications with encouraging outcomes. In the same cancers, PET/CT imaging by FAPIs are demonstrating to be valuable alternative to [18F]-FDG in assessment of cancers in which [18F]-FDG PET performance is suboptimal due to [18F]-FDG high background uptake or relatively low avidity. Furthermore, the propensity to specifically target FAP expression through FAP-targeted medications or radiotracer therapy creates prospects for image-guided treatment in both cancer and non-cancer indications. FAPI PET will remain a fascinating field of study in the future years.

Introduction: Accurate and automated assessment of anterior cruciate ligament (ACL) injuries in MR images is essential for athlete healthcare and rapid diagnosis of knee injuries. However, challenges such as the small size of the ligament, variations in MR image quality, and complex anatomical structures complicate the classification process.Methods: In this study, we propose a hierarchical deep learning model for the detection and classification of ACL injuries. The model consists of two main phases: ACL segmentation and injury classification. In the first phase, we employ an encoder-decoder architecture with attention mechanisms to accurately identify the ACL region in MR images, while suppressing background noise. Skip connections are used to preserve spatial details and improve segmentation accuracy. In the second phase, the segmented ACL region is input into a hierarchical convolutional neural network (CNN) for classification. Dense blocks are incorporated to maximize feature reuse, while max-pooling and global average pooling (GAP) layers help to reduce overfitting and improve feature extraction.Results: The proposed method was evaluated on a knee MRI dataset and compared with other state-of-the-art approaches. Our model demonstrated high accuracy in both segmentation and classification tasks, owing to the integration of attention mechanisms and hierarchical feature extraction.Conclusion: This approach offers a robust solution for the automated assessment of ACL injuries, providing clinicians and sports medicine specialists with a reliable tool for more efficient and accurate diagnosis.

[This corrects the article DOI: 10.34172/bi.30427.].

Introduction: Bhallataka (Semecarpus anacardium Linn.) is used in traditional medicine to treat various ailments. The nut extract of Bhallataka, known as Bhallataka taila, has anticancer properties. Although several studies have explored to verify and evaluate its anticancer properties and efficacy against various cancers, the specific target proteins, mode of action, and associated metabolites have not yet been identified. This study aimed to elucidate the biological mechanisms of Bhallataka taila using an integrated metabolomics and systems pharmacology approach with in vitro validation.Methods: Untargeted metabolomics using liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to evaluate the metabolites in Bhallataka taila, identify key protein targets and link them to cellular pathways through bioinformatics-based network pharmacology. Protein targets were mapped using BindingDB, and pathway enrichment was analyzed using STRINGdb. An in vitro study of A549 cells assessed the impact of Bhallataka taila on cellular viability (MTT assay), apoptosis (AO-EB staining), reactive oxygen species (ROS) production (fluorescent spectroscopy and DCFDA staining), and marker validation (immunoblotting and qRT-PCR). The integration of metabolomics, network pharmacology, and in vitro experiments offers a significant understanding of the anticancer mechanisms and pathways influenced by Bhallataka taila in non-small cell lung cancer (NSCLC) cells. Statistical analysis was performed using GraphPad Prism using one-way ANOVA.Results: Metabolomics combined with network pharmacology detected 2023 unique metabolites at the MS1 level and 216 metabolites at the MS2 level. Bhallataka taila metabolites were found to interact with 180 human target proteins identified through BindingDB analysis. These target proteins were mapped to key cancer regulatory signaling pathways, along with TNF-related apoptosis-inducing ligand (TRAIL), protease-activated receptor-1 (PAR1)-mediated thrombin signaling, Syndecan-1 and Glypican pathways, and vascular endothelial growth factor receptor (VEGFR)1/2 pathways. In vitro validation demonstrated that Bhallataka taila significantly regulated apoptosis (57%) and ROS production (56%) in A549 cells compared to control while modulating other cancer-related regulatory pathways.Conclusion: This data-driven study can help researchers identify promising cancer treatment candidates and validate their efficacy. This approach integrates traditional knowledge with modern scientific techniques to reinforce the anticancer potential of Bhallataka taila and its mechanisms.

Introduction: Doxorubicin (DOX) is a widely used first-line treatment for various cancers but causes toxicity. Targeted drug delivery systems, particularly DOX-encapsulated liposomes, show clinical success and lower toxicity. The abnormal angiogenesis in high-grade tumors, making it crucial to develop strategies that target this process in conjunction with chemotherapy. This study presents an innovative formulation of anti-VEGFR2-functionalized liposomal DOX, designed to reduce systemic drug release, enhance drug release and bioavailability at tumor sites, and reducing adverse effects, representing a promising advancement in targeted cancer therapy.Methods: Liposome formulations including liposome (Lip), DOX loaded liposome (Lip-DOX), anti VEGFR2 Nanobody-conjugated liposome (Lip-Nb), and anti VEGFR2 Nanobody- conjugated DOX-loaded liposome (Lip-DOX-Nb) were prepared by film hydration method and then fully characterized. The cellular uptake of these nanocarriers were assessed by flow cytometry analysis in human umbilical vein endothelial cells (HUVECs). Further, the ability of the different liposomal formulations to suppress angiogenesis were assessed by performing tube formation assay on HUVECs. In addition, the inhibitory impact of low dose consumption of the formulations to inhibit the migratory capacity of glioma cells were assessed by scratch migration assay on U87 cells.Results: The prepared liposomal formulations displayed optimal size range of 120-131 nm, with slightly negative charge about -2.4 mv, spherical morphology and effective encapsulation of about 91% of the total DOX and high conjugation efficiency of about 87% of total anti VEGFR2 Nb that are acceptable for nano sized targeted drug delivery systems. In vitro experiments; flow cytometry results verified cellular uptake of DOX loaded liposomes to HUVEC cell line and more cellular uptake was observed for Lip-DOX-Nb liposomes demonstrated that the anti-VEGFR2-conjugated liposomes enhance cellular uptake. Lip-DOX-Nb liposomes also showed more cytotoxicity effect against VEGFR2-positive HUVEC cells in compare with non-conjugated liposomes; effectively induced apoptosis to HUVEC cells and reduced the migratory capacity on U87 cancer cells. Analysis of the treated cells using DHM revealed that Lip-DOX-Nb enhanced nuclear integrity of U87 cancer cells while inducing cell death.Conclusion: This designed drug delivery system worked as strong anticancer and angiogenesis suppression agent ex-vitro angiogenesis model via VEGFR2 targeting.

The main objective of this research is to identify potential leads for developing potent Keap1 inhibitors. In the current research article, in-silico methods have been employed to discover potential Keap1 inhibitors. 3D-QSAR was generated using the ChemBL database of Keap1 inhibitors with IC50. The best pharmacophore was selected for the screening of three different libraries namely Asinex, MiniMaybridge, and Zinc. The molecules screened from the databases were filtered through druggability rules and molecular docking studies. The best binding molecules obtained after docking studies were subjected to physicochemical properties toxicity determination by in-silico methods. The best hits were studied for stability in the cavity of Keap1 by molecular dynamic simulations. The virtual screening of different databases was carried out separately and three leads, were obtained. These lead molecules ASINEX 508, MiniMaybridgeHTS_01719, and ZINC 0000952883 showed the best binding in the Keap1 cavity. The molecular dynamic simulations of the binding complexes of the leads support the docking analysis. The leads (ASINEX 508, MiniMaybridgeHTS_01719, and ZINC 0000952883) were stabilized in the Keap1 binding cavity throughout 100 ns simulation, with average RMSD values of 0.100, 0.114, and 0.106 nm, respectively. This research proposes three lead molecules as potential Keap1 inhibitors based on high throughput screening, docking, and MD simulation studies. These hit molecules can be used for further design and development of Keap1 inhibitors. This research provides the preliminary data for discovering novel Keap1 inhibitors. It opens new avenues for medicinal chemists to explore antioxidant-stimulating molecules targeting the Keap1-Nrf2 pathway.

Schizophrenia is a devastating chronic mental health illness which includes a complex set of symptoms like hallucination, illusion and delusion, and to manage, lifelong antipsychotic medications are needed. Schizophrenia affects 1% of the population worldwide, and to date, two different classes of antipsychotics, i.e., typical and atypical antipsychotics, are available in the market, and there is an urgent need for promising antipsychotic drugs. In this review, we focus on recently approved antipsychotics and then focus on different antipsychotic drugs under clinical trials. In this review, we first focus on lumateperone in detail, which was approved in December 2019 by the Food and Drug Administration (FDA) and simultaneously modulates serotonin, glutamate and dopamine neurotransmitters and is used at doses of 10.5-, 21- and 42 mg, which show mild adverse effects like constipation, sedation, somnolence and fatigue. This review also focuses on a few more emerging antipsychotics like brexpiprazole, brilaroxazine, roluperidone, F17464, pimavanserin (ACP-103), xanomeline, BI 409306, BI 425809 and MK-8189 which are under different phase of clinical trials and might get approved soon. Brexpiprazole and brilaroxazine act on dopamine receptors, whereas xanomeline, pimavanserin and roluperidone do not act on D2 receptors and manage the symptoms. All the antipsychotic drugs covered did not show any other severe adverse effects except gastrointestinal issues and cardiometabolic risk factors. However, still rigorous clinical trials and modifications are needed to manage adverse effects, and we can expect a few antipsychotics to be on the market soon.

Meniscus injuries in athletes' knee joints not only hinder performance but also pose substantial challenges in timely diagnosis and effective treatment. Delayed or inaccurate diagnosis often leads to prolonged recovery periods, exacerbating athletes' discomfort and compromising their ability to return to peak performance levels. Therefore, the accurate and timely diagnosis of meniscus injuries is crucial for athletes to receive appropriate treatment promptly and resume their training regimen effectively. This paper presents a multi-step approach for diagnosing meniscus injuries through segmentation of images into lesions regions, followed by a combined classification method. The present study employs a method whereby image noise is first reduced, followed by the implementation of an enhanced iteration of the U-Net algorithm to perform image segmentation and identify regions of interest for potential injury detection. In the context of diagnosing injury images, the extraction of features was accomplished through the utilization of the contour line method. Furthermore, the identification of injury types was facilitated through the application of the ensemble method, employing the principles of basic category-based voting. The method under consideration has been subjected to evaluation using a well-recognized dataset comprising MRI images knee joint injuries. The findings reveal that the efficacy of the proposed approach exhibits a significant enhancement in contrast to the newly developed techniques.

The current study reports the comparative stimuli-responsive synthesis of silver nanoparticles (AgNPs) with various sizes and morphologies employing Lycium ruthenicum extract and sodium citrate solutions. The morphology and size of AgNPs were regulated by varying the pH values, concentrations of the extract solution, and temperatures in the reaction medium. The prepared AgNPs were assessed via various instrumental analyses, including UV-Vis, FTIR, XRD, TEM, and DLS. The L. ruthenicum extract displayed several functional groups that reduced the Ag ions to the AgNPs at different values of pH. However, the primary chemical structure of L. ruthenicum was virtually unaltered at these conditions. Variations in the pH and extract concentration of the reaction medium yielded AgNPs of different sizes and morphologies. Both bio- and chemo-synthesized AgNPs revealed a relatively dispersed sphere-shaped morphology under alkaline conditions (≈ 36 nm). This study introduced a simple, valuable, and green technique for stimuli-sensitive AgNPs synthesis employing the L. ruthenicum extract.