Superoxide Dismutase-Mimetic Polyphenol-Based Carbon Dots for Multimodal Bioimaging and Treatment of Atopic Dermatitis.

Polyphenols have been investigated for their potential to mitigate inflammation in the context of atopic dermatitis (AD). In this study, epigallocatechin-3-gallate (EGCG)-based carbon dots (EGCG@CDs) were developed to enhance transdermal penetration, reduce inflammation, recapitulate superoxide dismutase (SOD) activity, and provide antimicrobial effects for AD treatment. The water-soluble EGCG@CDs in a few nanometers size exhibit a negative zeta potential, making them suitable for effective transdermal penetration. The fluorescence properties, including an upconversion effect, make EGCG@CDs suitable imaging probes for both in vitro and in vivo applications. By mimicking the SOD enzyme, EGCG@CDs scavenge reactive oxygen species (ROS) and actively produce hydrogen peroxide through a highly catalytic capability toward the oxygen reduction reaction, resulting in the inhibition of bacterial growth. The enhanced antioxidant properties, high charge mobility, and various functional groups of EGCG@CDs prove effective in reducing intracellular ROS in an in vitro AD model. In the mouse AD model, EGCG@CDs incorporated into a hydrogel actively penetrated the epidermal layer, leading to ROS scavenging, reduced mast cell activation, and histological recovery of skin barriers. This research represents the versatile potential of EGCG@CDs in addressing AD and advancing tissue engineering.

No-ozone cold plasma induces apoptosis in human neuroblastoma cell line via increased intracellular reactive oxygen species (ROS).

BACKGROUND: This study aimed to evaluate the effect of argon-based No-ozone Cold Plasma (NCP) on neuroblastoma cancer cell apoptosis. METHODS: Experiments were performed with SK-N-SH and HS 68. Cell cultures were treated with NCP for 1, 3, and 5 min. NCP was applied using three different strategies: direct NCP application to cell cultures, to only media, and to only cells. Evaluation of cell viability and the level of the reactive oxygen species (ROS) was performed. N-acetyl-L-cysteine (NAC) was also used to antagonize intracellular ROS. Cleaved caspase 3, PARP, aquaporin (AQP) 3 and 8 were detected. RESULTS: NCP induced a gradual decrease in the SK-N-SH cell viability. In contrast, the viability of HS 68 cells did not change. SK-N-SH cells viability was reduced the most when the only media-NCP application strategy was employed. Intracellular ROS levels were significantly increased with time. Cleaved caspase 3 and PARP were increased at 6 h after NCP application. SK-N-SH cells remained viable with NAC after NCP application. AQP 3 and 8 were over-expressed in SK-N-SH cells. CONCLUSION: These findings demonstrate the anti-cancer effect of NCP on neuroblastoma cells. NCP enhanced the selective apoptosis of neuroblastoma cells due to the increased intracellular ROS.

Oncolytic adenovirus as pancreatic cancer-targeted therapy: Where do we go from here?

Pancreatic cancer remains one of the deadliest cancers with extremely high mortality rate, and the number of cases is expected to steadily increase with time. Pancreatic cancer is refractory to conventional cancer treatment options, like chemotherapy and radiotherapy, and commercialized immunotherapeutics, owing to its immunosuppressive and desmoplastic phenotype. Due to these reasons, development of an innovative treatment option that can overcome these challenges posed by the pancreatic tumor microenvironment (TME) is in an urgent need. The present review aims to summarize the evolution of oncolytic adenovirus (oAd) engineering and usage as therapeutics (either monotherapy or combination therapy) over the last decade to overcome these hurdles to instigate a potent antitumor effect against desmoplastic and immunosuppressive pancreatic cancer.

Fully Automated Segmentation of Human Eyeball Using Three-Dimensional U-Net in T2 Magnetic Resonance Imaging.

Purpose: To develop and validate a fully automated deep-learning-based tool for segmentation of the human eyeball using a three-dimensional (3D) U-Net, compare its performance to semiautomatic segmentation ground truth and a two-dimensional (2D) U-Net, and analyze age and sex differences in eyeball volume, as well as gaze-dependent volume consistency in normal subjects. Methods: We retrospectively collected 474 magnetic resonance imaging (MRI) scans, including different gazing scans, from 119 patients. A 10-fold cross-validation was applied to separate the dataset into training, test, and validation sets for both the 3D U-Net and 2D U-Net. Performance accuracy was measured using four quantitative metrics compared to the ground truth, and Bland-Altman plot analysis was conducted. Age and sex differences in eyeball volume and variability in eyeball volume differences across gazing directions were analyzed. Results: The 3D U-Net outperformed the 2D U-Net with mean accuracy scores >0.95, showing acceptable agreement in the Bland-Altman plot analysis despite a tendency for slight overestimation (mean difference = -0.172 cm³). Significant sex differences and age effects on eyeball volume were observed for both methods (P < 0.05). No significant volume differences were found between the segmentation methods or within each method for the different gazing directions. Significant differences in performance accuracy were identified among the five gazing directions, with the upward direction showing a notably lower performance. Conclusions: Our study demonstrated the effectiveness of 3D U-Net human eyeball volume segmentation using T2-weighted MRI. The robustness and reliability of 3D U-Net across diverse populations and gaze directions support enhanced ophthalmic diagnosis and treatment strategies. Translational Relevance: Our findings demonstrate the feasibility of using the proposed 3D U-Net model for the automatic segmentation of the human eyeball, with potential applications in various ophthalmic research fields that require the analysis of 3D geometric eye globe shapes or eye movement detection.

Peptide Assembly of Different Dimensions and Their Effect on Myoblast Proliferation.

Variations in the functionalities of materials of different dimensions containing the same functional groups can be attributed to the structural stability and morphology of the materials. The morphology of peptide assemblies can influence their interactions with biological systems and ultimately modulate their bioactivity. Among reported Arg-Gly-Asp (RGD)-based supramolecular materials, two-dimensional (2-D) peptide assembly has been rarely studied. Herein, we report the fabrication of RGD-based supramolecular one-dimensional (1-D) and 2-D assemblies as peptide-based myoblast growth accelerators. The 2-D assembly was more effective in proliferating C2C12 cells than the 1-D assembly. These findings provide insights into the construction of optimal RGD-based supramolecular functional materials of different dimensions.

Detection of Multiple Respiration Patterns Based on 1D SNN from Continuous Human Breathing Signals and the Range Classification Method for Each Respiration Pattern.

Human respiratory information is being used as an important source of biometric information that can enable the analysis of health status in the healthcare domain. The analysis of the frequency or duration of a specific respiration pattern and the classification of respiration patterns in the corresponding section for a certain period of time are important for the utilization of respiratory information in various ways. Existing methods require window slide processing to classify sections for each respiration pattern from the breathing data for a certain time period. In this case, when multiple respiration patterns exist within one window, the recognition rate can be lowered. To solve this problem, a 1D Siamese neural network (SNN)-based human respiration pattern detection model and a merge-and-split algorithm for the classification of multiple respiration patterns in each region for all respiration sections are proposed in this study. When calculating the accuracy based on intersection over union (IOU) for the respiration range classification result for each pattern, the accuracy was found to be improved by approximately 19.3% compared with the existing deep neural network (DNN) and 12.4% compared with a 1D convolutional neural network (CNN). The accuracy of detection based on the simple respiration pattern was approximately 14.5% higher than that of the DNN and 5.3% higher than that of the 1D CNN.

Two-Dimensional Peptide Assembly via Arene-Perfluoroarene Interactions for Proliferation and Differentiation of Myoblasts.

Supramolecular assembly based on aromatic interactions can provide well-defined nanostructures with an understanding of intermolecular interactions at the molecular level. The peptide assembly via a supramolecular approach can overcome the inherent limitations of bioactive peptides, such as proteolytic degradations and rapid internalizations into the cytosol. Although extensive research has been carried out on supramolecular peptide materials with a two-dimensional (2D) structure, more needs to be reported on biological activity studies using well-defined 2D peptide materials. Physical and chemical properties of the 2D peptide assembly attributed to their large surface area and flexibility can show low cytotoxicity, enhanced molecular loading, and higher bioconjugation efficiency in biological applications. Here, we report supramolecular 2D materials based on the pyrene-grafted amphiphilic peptide, which contains a peptide sequence (Asp-Gly-Glu-Ala; DGEA) that is reported to bind to the integrin α2ß1 receptor in 2D cell membranes. The addition of octafluoronaphthalene (OFN) to the pyrene-grafted peptide could induce a well-ordered 2D assembly by face-centered arene-perfluoroarene stacking. The DGEA-peptide 2D assembly with a flat structure, structural stability against enzymatic degradations, and a larger size can enhance the proliferation and differentiation of muscle cells via continuous interactions with cell membrane receptors integrin α2ß1 showing a low intracellular uptake (15%) compared to that (62%) of the vesicular peptide assembly. These supramolecular approaches via the arene-perfluoroarene interaction provide a strategy to fabricate well-defined 2D peptide materials with an understanding of assembly at the molecular level for the next-generation peptide materials.

General psychopathology factor (p-factor) prediction using resting-state functional connectivity and a scanner-generalization neural network.

The general psychopathology factor (p-factor) represents shared variance across mental disorders based on psychopathologic symptoms. The Adolescent Brain Cognitive Development (ABCD) Study offers an unprecedented opportunity to investigate functional networks (FNs) from functional magnetic resonance imaging (fMRI) associated with the psychopathology of an adolescent cohort (n > 10,000). However, the heterogeneities associated with the use of multiple sites and multiple scanners in the ABCD Study need to be overcome to improve the prediction of the p-factor using fMRI. We proposed a scanner-generalization neural network (SGNN) to predict the individual p-factor by systematically reducing the scanner effect for resting-state functional connectivity (RSFC). We included 6905 adolescents from 18 sites whose fMRI data were collected using either Siemens or GE scanners. The p-factor was estimated based on the Child Behavior Checklist (CBCL) scores available in the ABCD study using exploratory factor analysis. We evaluated the Pearson's correlation coefficients (CCs) for p-factor prediction via leave-one/two-site-out cross-validation (LOSOCV/LTSOCV) and identified important FNs from the weight features (WFs) of the SGNN. The CCs were higher for the SGNN than for alternative models when using both LOSOCV (0.1631 ± 0.0673 for the SGNN vs. 0.1497 ± 0.0710 for kernel ridge regression [KRR]; p < 0.05 from a two-tailed paired t-test) and LTSOCV (0.1469 ± 0.0381 for the SGNN vs. 0.1394 ± 0.0359 for KRR; p = 0.01). It was found that (a) the default-mode and dorsal attention FNs were important for p-factor prediction, and (b) the intra-visual FN was important for scanner generalization. We demonstrated the efficacy of our novel SGNN model for p-factor prediction while simultaneously eliminating scanner-related confounding effects for RSFC.

Effect of No-ozone Cold Plasma on Regeneration after Crushed Mental Nerve Injury in rats.

Background: This experimental research aimed to determine whether No-ozone Cold Plasma (NCP) has regenerative effect on crushed injured sensory nerves in a rat model (Wistar A) and to evaluate whether NCP can be used as an alternative treatment method for sensory nerve injury in the oral-maxillofacial region. Methods: A total of 10 Wistar A rats were used for this experiment. They were divided into three groups according to whether the mental nerve of the left mandible was injured and NCP was applied or not: group 1 (n=3) (non-mental nerve damage, non-MD) - the left mental nerve was exposed and non-damaged; group 2 (n=3) (mental nerve damage, MD) - the left mental nerve was exposed and damaged, NCP was not applied; and group 3 (n=4) (mental nerve damage and NCP, MD-NCP) - the left mental nerve was exposed and damaged, NCP was applied with regular intervals (three times a week). Results: For the behavior analysis, von Frey test was used. Furthermore, the nerve tissues were examined with hematoxylin and eosin (H&E) staining, and the extent of neurorecovery was evaluated with the immunofluorescence staining of certain markers. The behavioral analysis showed that the function recovery sensory nerve was faster in group 3 (MD-NCP). In the histomorphologic and immunofluorescence analyses, the expression of the factors involved in neurorecovery was much higher in group 3 than in group 2 (MD). Conclusions: The expeditious recovery of sensory nerve function as well as the higher expression of the factors indicating nerve function recovery in the NCP-treated group suggest that NCP has a positive effect on regeneration after sensory nerve crushing injury. Therefore, in the case of sensory impairment of the oral-maxillofacial region, no-ozone cold plasma can be applied for therapeutic effect.

Recognition of 3D Chiral Microenvironments for Myoblast Differentiation.

Cell chirality plays a critical role in the linkage between molecular chirality and the asymmetrical biological functions of body organs. However, enantioselective interactions between cell chirality and the extracellular environment are not yet fully understood. In this study, we investigated the effects of structurally chiral extracellular microenvironments on cellular alignments and differentiations. Twisted wrinkle-shaped chiral micropatterns were prepared using biaxial and asymmetric buckling methods, wherein structural handedness was determined from the orientation of the tilt angle between the first and second microwrinkles. Myoblasts were separately cultured on two enantiomeric chiral micropatterns in a mirror-reflected shape. Cells cultured on the left-handed chiral micropatterns preferred alignments along the direction of the second microwrinkle, with a relatively deeper valley than that of the first microwrinkle. The aligned cells on the left-handed pattern showed higher differentiation rates, as assessed by fusion indices and marker protein expression levels, than those cultured on right-handed chiral micropatterns. These results suggest that myoblasts exhibit enantioselective recognition of structurally chiral microenvironments, which can promote cellular alignments and differentiation.

Current clinical landscape of oncolytic viruses as novel cancer immunotherapeutic and recent preclinical advancements.

Oncolytic viruses (OVs) have been gaining attention in the pharmaceutical industry as a novel immunotherapeutic and therapeutic adjuvant due to their ability to induce and boost antitumor immunity through multiple mechanisms. First, intrinsic mechanisms of OVs that enable exploitation of the host immune system (e.g., evading immune detection) can nullify the immune escape mechanism of tumors. Second, many types of OVs have been shown to cause direct lysis of tumor cells, resulting in an induction of tumor-specific T cell response mediated by release of tumor-associated antigens and danger signal molecules. Third, armed OV-expressing immune stimulatory therapeutic genes could be highly expressed in tumor tissues to further improve antitumor immunity. Last, these OVs can inflame cold tumors and their microenvironment to be more immunologically favorable for other immunotherapeutics. Due to these unique characteristics, OVs have been tested as an adjuvant of choice in a variety of therapeutics. In light of these promising attributes of OVs in the immune-oncology field, the present review will examine OVs in clinical development and discuss various strategies that are being explored in preclinical stages for the next generation of OVs that are optimized for immunotherapy applications.

ErbB3-Targeting Oncolytic Adenovirus Causes Potent Tumor Suppression by Induction of Apoptosis in Cancer Cells.

Cancer is a multifactorial and deadly disease. Despite major advancements in cancer therapy in the last two decades, cancer incidence is on the rise and disease prognosis still remains poor. Furthermore, molecular mechanisms of cancer invasiveness, metastasis, and drug resistance remain largely elusive. Targeted cancer therapy involving the silencing of specific cancer-enriched proteins by small interfering RNA (siRNA) offers a powerful tool. However, its application in clinic is limited by the short half-life of siRNA and warrants the development of efficient and stable siRNA delivery systems. Oncolytic adenovirus-mediated therapy offers an attractive alternative to the chemical drugs that often suffer from innate and acquired drug resistance. In continuation to our reports on the development of oncolytic adenovirus-mediated delivery of shRNA, we report here the replication-incompetent (dAd/shErbB3) and replication-competent (oAd/shErbB3) oncolytic adenovirus systems that caused efficient and persistent targeting of ErbB3. We demonstrate that the E1A coded by oAd/shErbB, in contrast to dAd/shErbB, caused downregulation of ErbB2 and ErbB3, yielding stronger downregulation of the ErbB3-oncogenic signaling axis in in vitro models of lung and breast cancer. These results were validated by in vivo antitumor efficacy of dAd/shErbB3 and oAd/shErbB3.

Bioreducible polymer-mediated delivery of oncolytic adenovirus can attenuate antiviral immune response and concurrently enhance the induction of antitumor immune response to effectively prevent metastasis.

Oncolytic virotherapy is a highly promising and novel treatment modality for cancer. Several clinical trials with oncolytic viruses have illustrated that the potent antitumor efficacy of these viruses may rely on the efficient induction of antitumor immune response. In contrast, antiviral immune response is attributed to adverse side defects and diminishing therapeutic efficacy. In the present report, we generated a nanohybrid complex incorporating immune stimulatory oncolytic adenovirus (oAd) co-expressing decorin (DCN) and interleukin (IL)-12 with a bioreducible nanomaterial composed of PEI-Arg-mPEG-S-S-mPEG-Arg-PEI blocks (PAPS), ultimately aiming to modulate both antitumor and antiviral immune responses to be favorable toward oncolytic virotherapy. The transduction efficacy of the PAPS-incorporated nanohybrid vector (Ad/PAPS) was significantly higher than that of a complex using our previously reported polymer PPSA (Ad/PPSA) regardless of the cellular coxsackievirus and adenovirus receptor expression level of cancer cells. oAd complexed with PAPS (oAd/PAPS) also elicited a more potent cancer cell killing effect, antitumor efficacy, and metastasis inhibition than naked oAd or oAd complexed with PPSA (oAd/PPSA) through a higher level of therapeutic transgenes (DCN and IL-12), viral replication, and more efficient infiltration of T cells into tumor tissues. Notably, oAd/PAPS induced the highest level of antitumor immune response while the antiviral immune response was mediated at a significantly lower level than those of naked oAd. Adaptive immune response against the virus was also significantly attenuated in the oAd/PAPS group. oAd/PAPS treatment also led to the highest level of antitumor central memory T cells and the lowest level of immunosuppressive regulatory T cells in the spleen. Collectively, our findings illustrate that oAd/PAPS can simultaneously regulate both antitumor and antiviral immune responses to be more favorable to oncolytic virotherapy, leading to improved gene expression, viral replication, and growth inhibition of both primary and metastatic tumors.

Challenges and progress toward tumor-targeted therapy by systemic delivery of polymer-complexed oncolytic adenoviruses.

Oncolytic adenovirus (oAd) elicits antitumor activity by preferential viral replication in cancer cells. However, poor systemic administrability or suboptimal intratumoral retainment of the virus remains a major challenge toward maximizing the antitumor activity of oAd in a clinical environment. To surmount these issues, a variety of non-immunogenic polymers has been used to modify the surface of oAds chemically or physically. Complexation of oAd with polymers can effectively evade the host immune response and reduces nonspecific liver sequestration. The tumor-specific delivery of these complexes can be further improved upon by inclusion of tumor-targeting moieties on the surface. Therefore, modification of the Ad surface using polymers is viewed as a potential strategy to enhance the delivery of Ad via systemic administration. This review aims to provide a comprehensive overview of polymer-complexed Ads, their progress, and future challenges in cancer treatment.

GM101 in Combination with Histone Deacetylase Inhibitor Enhances Anti-Tumor Effects in Desmoplastic Microenvironment.

Oncolytic adenoviruses (oAds) have been evaluated in numerous clinical trials due to their promising attributes as cancer therapeutics. However, the therapeutic efficacy of oAds was limited due to variable coxsackie and adenovirus receptor (CAR) expression levels and the dense extracellular matrix (ECM) of heterogenic clinical tumors. To overcome these limitations, our present report investigated the therapeutic efficacy of combining GM101, an oAd with excellent tumor ECM degrading properties, and histone deacetylase inhibitor (HDACi). Four different HDACi (suberohydroxamic acid (SBHA), MS-275, trichostatin A (TSA), and valproic acid) candidates in combination with replication-incompetent and GFP-expressing Ad (dAd/GFP) revealed that SBHA and MS-275 exerted more potent enhancement in Ad transduction efficacy than TSA or valproic acid. Further characterization revealed that SBHA and MS-275 effectively upregulated CAR expression in cancer cells, improved the binding of Ad with cancer cell membranes, and led to dynamin 2- and clathrin-mediated endocytosis of Ad. The combination of GM101 with HDACi induced superior cancer cell killing effects compared to any of the monotherapies, without any additional cytotoxicity in normal cell lines. Further, GM101+SBHA and GM101+MS-275 induced more potent antitumor efficacy than any monotherapy in U343 xenograft tumor model. Potent antitumor efficacy was achieved via the combination of GM101 with HDACi, inducing necrotic and apoptotic cancer cell death, inhibiting cancer cell proliferation, degrading ECM in tumor tissue, and thus exerting the highest level of virus dispersion and accumulation. Collectively, these data demonstrate that the combination of GM101 and HDACi can enhance intratumoral dispersion and accumulation of oAd through multifaced mechanisms, making it a promising strategy to address the challenges toward successful clinical development of oAd.

Optimal Method for Fetal Brain Age Prediction Using Multiplanar Slices From Structural Magnetic Resonance Imaging.

The accurate prediction of fetal brain age using magnetic resonance imaging (MRI) may contribute to the identification of brain abnormalities and the risk of adverse developmental outcomes. This study aimed to propose a method for predicting fetal brain age using MRIs from 220 healthy fetuses between 15.9 and 38.7 weeks of gestational age (GA). We built a 2D single-channel convolutional neural network (CNN) with multiplanar MRI slices in different orthogonal planes without correction for interslice motion. In each fetus, multiple age predictions from different slices were generated, and the brain age was obtained using the mode that determined the most frequent value among the multiple predictions from the 2D single-channel CNN. We obtained a mean absolute error (MAE) of 0.125 weeks (0.875 days) between the GA and brain age across the fetuses. The use of multiplanar slices achieved significantly lower prediction error and its variance than the use of a single slice and a single MRI stack. Our 2D single-channel CNN with multiplanar slices yielded a significantly lower stack-wise MAE (0.304 weeks) than the 2D multi-channel (MAE = 0.979, p < 0.001) and 3D (MAE = 1.114, p < 0.001) CNNs. The saliency maps from our method indicated that the anatomical information describing the cortex and ventricles was the primary contributor to brain age prediction. With the application of the proposed method to external MRIs from 21 healthy fetuses, we obtained an MAE of 0.508 weeks. Based on the external MRIs, we found that the stack-wise MAE of the 2D single-channel CNN (0.743 weeks) was significantly lower than those of the 2D multi-channel (1.466 weeks, p < 0.001) and 3D (1.241 weeks, p < 0.001) CNNs. These results demonstrate that our method with multiplanar slices accurately predicts fetal brain age without the need for increased dimensionality or complex MRI preprocessing steps.

White matter hyperintensities segmentation using the ensemble U-Net with multi-scale highlighting foregrounds.

White matter hyperintensities (WMHs) are abnormal signals within the white matter region on the human brain MRI and have been associated with aging processes, cognitive decline, and dementia. In the current study, we proposed a U-Net with multi-scale highlighting foregrounds (HF) for WMHs segmentation. Our method, U-Net with HF, is designed to improve the detection of the WMH voxels with partial volume effects. We evaluated the segmentation performance of the proposed approach using the Challenge training dataset. Then we assessed the clinical utility of the WMH volumes that were automatically computed using our method and the Alzheimer's Disease Neuroimaging Initiative database. We demonstrated that the U-Net with HF significantly improved the detection of the WMH voxels at the boundary of the WMHs or in small WMH clusters quantitatively and qualitatively. Up to date, the proposed method has achieved the best overall evaluation scores, the highest dice similarity index, and the best F1-score among 39 methods submitted on the WMH Segmentation Challenge that was initially hosted by MICCAI 2017 and is continuously accepting new challengers. The evaluation of the clinical utility showed that the WMH volume that was automatically computed using U-Net with HF was significantly associated with cognitive performance and improves the classification between cognitive normal and Alzheimer's disease subjects and between patients with mild cognitive impairment and those with Alzheimer's disease. The implementation of our proposed method is publicly available using Dockerhub (https://hub.docker.com/r/wmhchallenge/pgs).

Overcoming the barriers to optimization of adenovirus delivery using biomaterials: Current status and future perspective.

Adenovirus (Ad) is emerging as a promising modality for cancer gene therapy due to its ability to induce high level of therapeutic transgene expression with no risk of insertional mutagenesis, ability to be facilely produced at a high titer, and capacity to induce robust antitumor immune response. Despite these excellent attributes of human serotype 5 Ad, poor systemic administration capability, coxsackie and adenovirus receptor (CAR)-dependent endocytic mechanism limiting potentially targetable cell types, nonspecific shedding to normal organs, and poor viral persistence in tumor tissues are major hindrances toward maximizing the therapeutic benefit of Ad in clinical setting. To address the abovementioned shortcomings, various non-immunogenic nanomaterials have been explored to modify Ad surface via physical or chemical interactions. In this review, we summarize the recent developments of different types of nanomaterials that had been utilized for modification of Ad and how tumor-targeted local and system delivery can be achieved with these nanocomplexes. Finally, we conclude by highlighting the key features of various nanomaterials-coated Ads and their prospects to optimize the delivery of virus.

Fetal Cortical Plate Segmentation Using Fully Convolutional Networks With Multiple Plane Aggregation.

Fetal magnetic resonance imaging (MRI) has the potential to advance our understanding of human brain development by providing quantitative information of cortical plate (CP) development in vivo. However, for a reliable quantitative analysis of cortical volume and sulcal folding, accurate and automated segmentation of the CP is crucial. In this study, we propose a fully convolutional neural network for the automatic segmentation of the CP. We developed a novel hybrid loss function to improve the segmentation accuracy and adopted multi-view (axial, coronal, and sagittal) aggregation with a test-time augmentation method to reduce errors using three-dimensional (3D) information and multiple predictions. We evaluated our proposed method using the ten-fold cross-validation of 52 fetal brain MR images (22.9-31.4 weeks of gestation). The proposed method obtained Dice coefficients of 0.907 ± 0.027 and 0.906 ± 0.031 as well as a mean surface distance error of 0.182 ± 0.058 mm and 0.185 ± 0.069 mm for the left and right, respectively. In addition, the left and right CP volumes, surface area, and global mean curvature generated by automatic segmentation showed a high correlation with the values generated by manual segmentation (R 2 > 0.941). We also demonstrated that the proposed hybrid loss function and the combination of multi-view aggregation and test-time augmentation significantly improved the CP segmentation accuracy. Our proposed segmentation method will be useful for the automatic and reliable quantification of the cortical structure in the fetal brain.

Oncolytic Viruses and Immune Checkpoint Inhibitors: Preclinical Developments to Clinical Trials.

Immuno-oncology (IO) has been an active area of oncology research. Following US FDA approval of the first immune checkpoint inhibitor (ICI), ipilimumab (human IgG1 k anti-CTLA-4 monoclonal antibody), in 2011, and of the first oncolytic virus, Imlygic (talimogene laherparepvec), in 2015, there has been renewed interest in IO. In the past decade, ICIs have changed the treatment paradigm for many cancers by enabling better therapeutic control, resuming immune surveillance, suppressing tumor immunosuppression, and restoring antitumor immune function. However, ICI therapies are effective only in a small subset of patients and show limited therapeutic potential due to their inability to demonstrate efficacy in 'cold' or unresponsive tumor microenvironments (TMEs). Relatedly, oncolytic viruses (OVs) have been shown to induce antitumor immune responses, augment the efficacy of existing cancer treatments, and reform unresponsive TME to turn 'cold' tumors 'hot,' increasing their susceptibility to checkpoint blockade immunotherapies. For this reason, OVs serve as ideal complements to ICIs, and multiple preclinical studies and clinical trials are demonstrating their combined therapeutic efficacy. This review will discuss the merits and limitations of OVs and ICIs as monotherapy then progress onto the preclinical rationale and the results of clinical trials of key combination therapies.