A cocktail nanovaccine targeting key entry glycoproteins elicits high neutralizing antibody levels against EBV infection.

Epstein-Barr virus (EBV) infects more than 95% of adults worldwide and is closely associated with various malignancies. Considering the complex life cycle of EBV, developing vaccines targeting key entry glycoproteins to elicit robust and durable adaptive immune responses may provide better protection. EBV gHgL-, gB- and gp42-specific antibodies in healthy EBV carriers contributed to sera neutralizing abilities in vitro, indicating that they are potential antigen candidates. To enhance the immunogenicity of these antigens, we formulate three nanovaccines by co-delivering molecular adjuvants (CpG and MPLA) and antigens (gHgL, gB or gp42). These nanovaccines induce robust humoral and cellular responses through efficient activation of dendritic cells and germinal center response. Importantly, these nanovaccines generate high levels of neutralizing antibodies recognizing vulnerable sites of all three antigens. IgGs induced by a cocktail vaccine containing three nanovaccines confer superior protection from lethal EBV challenge in female humanized mice compared to IgG elicited by individual NP-gHgL, NP-gB and NP-gp42. Importantly, serum antibodies elicited by cocktail nanovaccine immunization confer durable protection against EBV-associated lymphoma. Overall, the cocktail nanovaccine shows robust immunogenicity and is a promising candidate for further clinical trials.

In Situ Array Microextraction and Metabolic Profiling of Small Extracellular Vesicles to Guide and Monitor Maternal Delivery.

The advantages of small extracellular vesicles (sEV) in disease management have become increasingly prominent, with the main challenge lying in meeting the demands of large-scale extraction and high-throughput analysis, a crucial aspect in the realm of precision medicine. To overcome this challenge, an engineered on-plate aptamer array (16×24 spots) is developed for continuous scale-up microextraction of plasma sEV and their in situ metabolic analysis using mass spectrometry. With this integrated array strategy, metabolic profiles of sEV are acquired from the plasma of 274 antenatal or postpartum women, reducing analysis time by half (7.5 h) and sample volume by 95% (only 0.125 µL usage) compared to the traditional suspension method. Moreover, using machine learning algorithms on sEV metabolic profiles, a risk score system is constructed that accurately assesses the need for epidural analgesia during childbirth and the likelihood of post-administration fever. The system, based on admission samples, achieves an impressive 94% accuracy. Furthermore, post-administration fever can be identified from delivery samples, reaching an overall accuracy rate of 88%. This work offers real-time monitoring of the childbirth process that can provide timely guidance for maternal delivery, underscoring the significance of sEV detection in large-scale clinical samples for medicine innovation and advancement.

Radiomics Analysis of Quantitative Maps from Synthetic MRI for Predicting Grades and Molecular Subtypes of Diffuse Gliomas.

PURPOSE: To investigate the feasibility of using radiomics analysis of quantitative maps from synthetic MRI to preoperatively predict diffuse glioma grades, isocitrate dehydrogenase (IDH) subtypes, and 1p/19q codeletion status. METHODS: Data from 124 patients with diffuse glioma were used for analysis (n = 87 for training, n = 37 for testing). Quantitative T1, T2, and proton density (PD) maps were obtained using synthetic MRI. Enhancing tumour (ET), non-enhancing tumour and necrosis (NET), and peritumoral edema (PE) regions were segmented followed by manual fine-tuning. Features were extracted using PyRadiomics and then selected using Levene/T, BorutaShap and maximum relevance minimum redundancy algorithms. A support vector machine was adopted for classification. Receiver operating characteristic curve analysis and integrated discrimination improvement analysis were implemented to compare the performance of different radiomics models. RESULTS: Radiomics models constructed using features from multiple tumour subregions (ET + NET + PE) in the combined maps (T1 + T2 + PD) achieved the highest AUC in all three prediction tasks, among which the AUC for differentiating lower-grade and high-grade diffuse gliomas, predicting IDH mutation status and predicting 1p/19q codeletion status were 0.92, 0.95 and 0.86 respectively. Compared with those constructed on individual T1, T2, and PD maps, the discriminant ability of radiomics models constructed on the combined maps separately increased by 11, 17 and 10% in predicting glioma grades, 35, 52 and 19% in predicting IDH mutation status, and 16, 15 and 14% in predicting 1p/19q codeletion status (p < 0.05). CONCLUSION: Radiomics analysis of quantitative maps from synthetic MRI provides a new quantitative imaging tool for the preoperative prediction of grades and molecular subtypes in diffuse gliomas.

Serological Exosome Metabolic Biopsy of Hepatocellular Carcinoma via Designed Core-Shell Nanoparticles.

Exosome metabolite-based liquid biopsy is a promising strategy for large-scale application in practical clinics toward precise medicine. Given the current challenges in successive isolation and analysis of exosomes and their metabolites in this field, we established a low-cost, high-throughput, and rapid platform for serological exosome metabolic biopsy of hepatocellular carcinoma (HCC) via designed core-shell nanoparticles. It starts with the efficient extraction of high-quality serum exosomes and exosome metabolic features, based on which significantly obvious sample clusters are observed by unsupervised cluster analysis. The following integration of feature selection and supervised machine learning enables the identification of six key metabolites and achieves high-performance prediction between HCC, liver cirrhosis, and healthy controls. Specifically, both sensitivity and accuracy achieve 100% among any pairwise intergroup discrimination in a blind test. The quality and reliability of six key metabolites are further evaluated and validated by using different machine learning algorithms and pathway exploration. Our platform contributes to the future growth of new liquid biopsy technologies for precision diagnosis and real-time monitoring of HCC, among other conditions.

Heterogeneous MXene Hybrid-Oriented Exosome Isolation and Metabolic Profiling for Early Screening, Subtyping and Follow-up Evaluation of Bladder Cancer.

Exosome metabolite-based noninvasive liquid biopsy is an emerging research hotspot that tends to substitute current means in clinics. Nanostructure-based mass spectrometry enables continuous exosome isolation and metabolic profiling with superior analysis speed and high efficiency. Herein, we construct a heterogeneous MXene hybrid that possesses ternary binding sites for exosome capture and outstanding matrix performance for metabolite analysis. Upon optimizing experimental conditions, the average extraction of exosomes and their metabolic patterns from a 60 mL urine sample is completed within 45 s (40 samples per batch for 30 min). According to the exosomal metabolic patterns and the subsequently established biomarker panel, we distinguish early bladder cancer (BCa) from healthy controls with an area under the curve (AUC) value greater than 0.995 in model training and validation sets. As well, we realize subtype classification of BCa in the blind test on metabolic patterns, with an AUC value of 0.867. We also explore the significant biomarkers that are sensitive to follow-up patients, which indeed present reverse change levels compared with pathological progression. This study has the potential to guide the development of the liquid biopsy approach.

Transcriptomic characterization of interactions between sodium selenite and coenzyme Q10 on preventing cadmium-induced testicular defects.

The effect of heavy metal cadmium (Cd) on testicular function is recognized. However, the mechanism involved is not well-established. In the present study, we analyzed the testicular transcriptomic changes induced by acute Cd exposure of adult rats with and without supplementation of antioxidants selenium (Se) and/or coenzyme Q10 (CoQ). Cd significantly decreased serum testosterone and two steroidogenic proteins SCARB1 and STAR. RNA-Seq analyses of testicular RNAs revealed specific activation of oxidative stress-, inflammation-, MAPK- and NF-κB-related signaling molecules. In addition, Cd treatment down-regulated gene for I, III and IV complexes of mitochondrial electron transport chain and up-regulated genes for NADPH-oxidase, major cascade in ROS production. The decrease in steroidogenesis and increase in inflammation may result from oxidative stress since supplementation of Se and CoQ, but not with either alone, almost completely prevented these changes, including overall alterations in transcriptome. Cd exposure induced total of 1192 differentially expressed genes (DEGs), which was reduced to 29 without considering confounding factors associated with Se/CoQ, a 97.6% protection rate. In conclusion, Cd exposure inhibited Leydig cell steroidogenesis by down-regulating SCARB1 and STAR through increasing oxidative stress and inflammation, but Se plus CoQ synergistically prevented all the changes induced by the Cd exposure.

Metabolic profiling of urinary exosomes for systemic lupus erythematosus discrimination based on HPL-SEC/MALDI-TOF MS.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disease which leads to the formation of immune complex deposits in multiple organs and has heterogeneous clinical manifestations. Currently, exosomes for liquid biopsy have been applied in diagnosis and monitoring of diseases, whereas SLE discrimination based on exosomes at the metabolic level is rarely reported. Herein, we constructed a protocol for metabolomic study of urinary exosomes from SLE patients and healthy controls (HCs) with high efficiency and throughput. Exosomes were first obtained by high-performance liquid size-exclusion chromatography (HPL-SEC), and then metabolic fingerprints of urinary exosomes were extracted by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) with high throughput and high efficency. With the statistical analysis by orthogonal partial least-squares discriminant analysis (OPLS-DA) model, SLE patients were efficiently distinguished from HCs, the area under the curve (AUC) of the receiver characteristic curve (ROC) was 1.00, and the accuracy of the unsupervised clustering heatmap was 90.32%. In addition, potential biomarkers and related metabolic pathways were analyzed. This method, with the characteristics of high throughput, high efficiency, and high accuracy, will provide the broad prospect of exosome-driven precision medicine and large-scale screening in clinical applications.

Cerebral delivery of redox-responsive lenalidomide prodrug plus methotrexate for primary central nerve system lymphoma combination therapy.

Primary central nervous system lymphoma (PCNSL) is an extremely malignant CNS tumor with high incidence and mortality rates. Its chemotherapy in the clinic has been restricted owing to unsatisfactory drug distribution in the cerebral tissues. In this study, a redox-responsive prodrug of disulfide-lenalidomide-methoxy polyethylene glycol (LND-DSDA-mPEG) was successfully developed for the cerebral delivery of lenalidomide (LND), and methotrexate (MTX) via subcutaneous (s.c.) administration at the neck for combined anti-angiogenesis and chemotherapy on PCNSL. Both the subcutaneous xenograft tumor model and orthotopic intracranial tumor model demonstrated that the co-delivery of LND and MTX nanoparticles (MTX@LND NPs) may significantly inhibit the growth of lymphoma and effectively prevent liver metastasis by downregulating CD31 and VEGF expression. Moreover, an orthotopic intracranial tumor model further verified that through s.c. administration at the neck, redox-responsive MTX@LND NPs could bypass the blood-brain barrier (BBB), efficiently distribute into brain tissues, and effectively inhibit lymphoma growth in the brain, as detected by magnetic resonance imaging (MRI). Taken together, this biodegradable, biocompatible, and redox-responsive nano-prodrug with highly effective targeted delivery of LND and MTX in the brain through the lymphatic vasculature may provide a facile and feasible treatment strategy for PCNSL in the clinic.

CCR7 Mediated Mimetic Dendritic Cell Vaccine Homing in Lymph Node for Head and Neck Squamous Cell Carcinoma Therapy.

Immunotherapy has been recognized as one of the most promising treatment strategies for head and neck squamous cell carcinoma (HNSCC). As a pioneering trend of immunotherapy, dendritic cell (DC) vaccines have displayed the ability to prime an immune response, while the insufficient immunogenicity and low lymph node (LN) targeting efficiency, resulted in an unsubstantiated therapeutic efficacy in clinical trials. Herein, a hybrid nanovaccine (Hy-M-Exo) is developed via fusing tumor-derived exosome (TEX) and dendritic cell membrane vesicle (DCMV). The hybrid nanovaccine inherited the key protein for lymphatic homing, CCR7, from DCMV and demonstrated an enhanced efficiency of LN targeting. Meanwhile, the reserved tumor antigens and endogenous danger signals in the hybrid nanovaccine activated antigen presenting cells (APCs) elicited a robust T-cell response. Moreover, the nanovaccine Hy-M-Exo displayed good therapeutic efficacy in a mouse model of HNSCC. These results indicated that Hy-M-Exo is of high clinical value to serve as a feasible strategy for antitumor immunotherapy.

Effects of aging and macrophages on mice stem Leydig cell proliferation and differentiation in vitro.

Background: Testosterone plays a critical role in maintaining reproductive functions and well-beings of the males. Adult testicular Leydig cells (LCs) produce testosterone and are generated from stem Leydig cells (SLCs) during puberty through adulthood. In addition, macrophages are critical in the SLC regulatory niche for normal testicular function. Age-related reduction in serum testosterone contributes to a number of metabolic and quality-of-life changes in males, as well as age-related changes in immunological functions. How aging and testicular macrophages may affect SLC function is still unclear. Methods: SLCs and macrophages were purified from adult and aged mice via FACS using CD51 as a marker protein. The sorted cells were first characterized and then co-cultured in vitro to examine how aging and macrophages may affect SLC proliferation and differentiation. To elucidate specific aging effects on both cell types, co-culture of sorted SLCs and macrophages were also carried out across two ages. Results: CD51+ (weakly positive) and CD51++ (strongly positive) cells expressed typical SLC and macrophage markers, respectively. However, with aging, both cell types increased expression of multiple cytokine genes, such as IL-1b, IL-6 and IL-8. Moreover, old CD51+ SLCs reduced their proliferation and differentiation, with a more significant reduction in differentiation (2X) than proliferation (30%). Age matched CD51++ macrophages inhibited CD51+ SLC development, with a more significant reduction in old cells (60%) than young (40%). Crossed-age co-culture experiments indicated that the age of CD51+ SLCs plays a more significant role in determining age-related inhibitory effects. In LC lineage formation, CD51+ SLC had both reduced LC lineage markers and increased myoid cell lineage markers, suggesting an age-related lineage shift for SLCs. Conclusion: The results suggest that aging affected both SLC function and their regulatory niche cell, macrophages.

Nanovaccines Fostering Tertiary Lymphoid Structure to Attack Mimicry Nasopharyngeal Carcinoma.

Tertiary lymphoid structures (TLSs) are formed in inflamed tissues, and recent studies demonstrated that the appearance of TLSs in tumor sites is associated with a good prognosis for tumor patients. However, the process of natural TLSs' formation was slow and uncontrollable. Herein, we developed a nanovaccine consisting of Epstein-Barr virus nuclear antigen 1 (EBNA1) and a bi-adjuvant of Mn2+ and cytosine-phosphate-guanine (CpG) formulated with tannic acid that significantly inhibited the development of mimicry nasopharyngeal carcinoma by fostering TLS formation. The nanovaccine activated LT-α and LT-ß pathways, subsequently enhancing the expression of downstream chemokines, CCL19/CCL21, CXCL10 and CXCL13, in the tumor microenvironment. In turn, normalized blood and lymph vessels were detected in the tumor tissues of the nanovaccine group, correlated with increased infiltration of lymphocytes. Especially, the proportion of the B220+ CD8+ T, which was produced via trogocytosis between T and B cells during activation of T cells, was increased in tumors of the nanovaccine group. Furthermore, the intratumoral effector memory T cells (Tem), CD45+, CD3+, CD8+, CD44+, and CD62L-, did not decrease after blocking the egress of T cells from tumor-draining lymph nodes by FTY-720. These results demonstrated that the nanovaccine can foster TLS formation, which thus enhances local immune responses significantly, delays tumor outgrowth, and prolongs the median survival time of murine models of mimicry nasopharyngeal carcinoma, demonstrating a promising strategy for nanovaccine development.

Carrier-free subunit nanovaccine amplifies immune responses against tumors and viral infections.

Codelivering subunit antigens and Toll-like receptor (TLR) molecular adjuvants via nanocarriers can stimulate potent innate and specific immune responses. Simple and effective nanovaccines fabrication is crucial for application. However, most nanovaccines were fabricated by introducing additional delivery materials, increasing safety risk, cost and processing complexity. Herein, a carrier-free nanovaccine was facilely prepared using a TLR1/TLR2 adjuvant, Diprovocim, rich in benzene rings that could interact with aromatic residues in subunit antigens through π-π stacking without additional materials. The carrier-free nanovaccines with a narrow size distribution could target lymph nodes (LNs) after intravenous injection to mice. The carrier-free nanovaccines based on ovalbumin (OVA) can stimulate strong antibody titers and CD4+ and CD8+ T cell immune responses in mice, and it synergized with anti-PD1 showing a potent tumor suppression in B16F10-OVA tumor model of mice. Furthermore, the carrier-free nanovaccine with glycoprotein E (gE), a glycoprotein of the varicella-zoster virus (VZV), also showed potent humoral and cellular immune responses. Therefore, using subunit proteins to support Diprovocim by π-π stacking provides a new approach for the preparation and application of novel vaccines for tumor therapy and prevention of infectious diseases. STATEMENT OF SIGNIFICANCE: Codelivering subunit antigens and adjuvants via nanocarriers stimulate potent innate and specific immune responses. However, existing delivery materials for fabricating nanovaccines will inevitably increase the cost of preparation, controllability, process complexity and safety assessment. Therefore, this study easily prepared carrier-free nanovaccines using the benzene ring-rich TLR1/TLR2 adjuvant Diprovocim, which can interact with aromatic residues in subunit antigens via π-π stacking without additional materials. The carrier-free nanovaccines of OVA demonstrated a potent tumor inhibition in treating melanoma in combination with anti-PD1. And the nanovaccines of gE stimulated a strong antibody titer and cellular immune response for herpes zoster. Thus, the present study provides a new approach for the preparation of subunit vaccines to combat various cancers and virus infections.

Nanoadjuvants Actively targeting lymph node conduits and blocking tumor invasion in lymphatic vessels.

Great efforts have been made to manipulate nanoparticles (NPs) with a diameter of 10-100 nm to passively target lymph nodes (LNs) to magnitude anti-tumor activity of T cells. However, no attention has been paid to increasing the retention of NPs with active affinity in order to induce a prolonged release of antigens or molecular adjuvants in the LNs mattering the immune response. Here, we formulated two NPs encapsulated with imiquimod (IMQ), a TLR7/8 agonist, and paclitaxel (PTX) and further modified them with tannic acid (TA), respectively, to generate IMQ NP and PTX NP with a final diameter of approximately 40 nm. Attributing a strong affinity of TA molecules to the elastin of LN conduits, the TA modified IMQ NPs can bypass the gaps in the layer of lymphatic endothelial cells and enter the paracortex through the lymph node capsule-associated (LNC) conduits. Similarly, the TA modified PTX NPs increased delivery of PTX to the metastatic tumor site in LNs, where the tumor-associated antigens were released and presented by conduits-lining dendritic cells to activate T cells. Thus, the NPs with deposition to LN conduits showed excellent performance in preventing lymphovascular invasion of triple-negative breast cancer cells and lung metastasis thereafter. On the contrary, the NPs without TA flowed through the subcutaneous sinus existing LNs directly by efferent lymphatic vessels showing relatively poor therapeutic outcomes. This study reveals that TA may mediate the long retention of antigens and molecular adjuvants to be delivered to deep LNs for developing potent vaccination technology.

Diagnosing, Typing, and Staging of Renal Cell Carcinoma by Designer Matrix-Based Urinary Metabolic Analysis.

Molecular diagnosing, typing, and staging have been considered to be the ideal alternatives of imaging-based detection methods in clinics. Designer matrix-based analytical tools, with high speed, throughout, efficiency and low/noninvasiveness, have attracted much attention recently for in vitro metabolite detection. Herein, we develop an advanced metabolic analysis tool based on highly porous metal oxides derived from available metal-organic frameworks (MOFs), which elaborately inherit the morphology and porosity of MOFs and newly incorporate laser adsorption capacity of metal oxides. Through optimized conditions, direct high-quality fingerprinting spectra in 0.5 µL of urine are acquired. Using these fingerprinting spectra, we can discriminate the renal cell carcinoma (RCC) from healthy controls with higher than 0.99 of area under the curve (AUC) values (R2Y(cum) = 0.744, Q2 (cum) = 0.880), as well, from patients with other tumors (R2Y(cum) = 0.748, Q2(cum) = 0.871). We also realize the typing of three RCC subtypes, including clear cell RCC, chromophobe RCC (R2Y(cum) = 0.620, Q2(cum) = 0.656), and the staging of RCC (R2Y(cum) = 0.755, Q2(cum) = 0.857). Moreover, the tumor sizes (threshold value is 3 cm) can be remarkably recognized by this advanced metabolic analysis tool (R2Y(cum) = 0.710, Q2(cum) = 0.787). Our work brings a bright prospect for designer matrix-based analytical tools in disease diagnosis, typing and staging.

Proteome Informatics in Tibetan Sheep (Ovis aries) Testes Suggest the Crucial Proteins Related to Development and Functionality.

Testis has an indispensable function in male reproduction of domestic animals. Tibetan sheep (Ovis aries) is a locally adapted breed of sheep raised in the Qinghai-Tibet Plateau, with outsized roles in providing the livelihood for millions of residents. Nevertheless, less is known on how protein expression and their functional roles in developmental testes of such breed limit their use in breeding efforts. In this study, we obtained comprehensive protein profiles from testes of Tibetan sheep at three developmental stages (including pre-puberty, post-puberty, and adulthood) using data-independent acquisition-based proteomic strategy to quantitatively identify the differentially abundant proteins (DAPs) associated with testicular development and function and to unravel the molecular basis of spermatogenesis. A total of 6,221 proteins were differentially expressed in an age-dependent manner. The reliability of the gene expression abundance was corroborated by quantitative PCR and targeted parallel reaction monitoring. These DAPs were significantly enriched to biological processes concerning spermatid development and sperm deformation, mitosis, glycolytic process, cell-cell/extracellular matrix (ECM) junctions, cell proliferation, apoptosis, and migration and to the pathways including, developmental process and sexual reproduction-related (such as VEGF, estrogen, insulin, GnRH, Hippo, PI3K-Akt, mTOR, MAPK, and AMPK), and testicular cell events-related pathways (such as tight/gap/adherens junctions, ECM-receptor interaction, regulation of actin cytoskeleton, glycolysis, cell cycle, and meiosis). Based on these bioinformatics analysis, we constructed four protein-protein interaction network, among which the proteins are involved in mitosis, meiosis, spermiogenesis, and testicular microenvironment, respectively. Altogether, these bioinformatics-based sequencing results suggest that many protein-coding genes were expressed in a development-dependent manner in Tibetan sheep testes to contribute to the testicular cell development and their surrounding microenvironment remodeling at various stages of spermatogenesis. These findings have important implications for further understanding of the mechanisms underlying spermatogenesis in sheep and even other plateau-adapted animals.

Exosome Metabolic Patterns on Aptamer-Coupled Polymorphic Carbon for Precise Detection of Early Gastric Cancer.

Gastric cancer (GC) presents high mortality worldwide because of delayed diagnosis. Currently, exosome-based liquid biopsy has been applied in diagnosis and monitoring of diseases including cancers, whereas disease detection based on exosomes at the metabolic level is rarely reported. Herein, the specific aptamer-coupled Au-decorated polymorphic carbon (CoMPC@Au-Apt) is constructed for the capture of urinary exosomes from early GC patients and healthy controls (HCs) and the subsequent exosome metabolic pattern profiling without extra elution process. Combining with machine learning algorithm on all exosome metabolic patterns, the early GC patients are excellently discriminated from HCs, with an accuracy of 100% for both the discovery set and blind test. Ulteriorly, three key metabolic features with clear identities are determined as a biomarker panel, obtaining a more than 90% diagnostic accuracy for early GC in the discovery set and validation set. Moreover, the change law of the key metabolic features along with GC development is revealed through making a comparison among HCs and GC at early stage and advanced stage, manifesting their monitoring ability toward GC. This work illustrates the high specificity of exosomes and the great prospective of exosome metabolic analysis in disease diagnosis and monitoring, which will promote exosome-driven precision medicine toward practical clinical application.

NIR-II Responsive Molybdenum Dioxide Nanosystem Manipulating Cellular Immunogenicity for Enhanced Tumor Photoimmunotherapy.

Photothermal therapy (PTT) in the second near-infrared (NIR-II) window has emerged as a better candidate for deep-tissue tumor elimination. More interestingly, the photothermal ablated tumor cells also manifest somewhat immunostimulation potency to elicit antitumor immunity, although most dying cells are undergoing apoptosis that is commonly considered as immunologically silent. Here, a NIR-II responsive nanosystem is established for tumor photoimmunotherapy using molybdenum dioxide (MoO2) nanodumbbells as the nanoconverter. Meanwhile, an apoptosis-blocking strategy is proposed to regulate the cell death pattern under NIR-II laser irradiation in order to improve the immunogenic cell death. The nanoformulation can efficiently block caspase 8-dependent apoptotic pathway in photothermal ablated tumor cells and transform into more immunogenic death patterns, thereby activating systemic immunity to inhibit tumor growth and metastasis. In addition, this strategy also helps enhance the body's responses to α-PD-1 immune checkpoint inhibitor, which implies a potential optimal combination for cancer immunotherapy.

Fabrication of subunit nanovaccines by physical interaction.

Vaccines can improve the quality of human life by preventing the burden of infectious diseases. Also, vaccination is becoming a powerful medication for preventing and treating tumors. Various vaccines have been developed based on the origin of the antigens. Herein, we focus on the subunit vaccines whose antigens are proteins or peptides. The advantage of subunit vaccines is safety for recipients; however, the immunogenicity of subunit antigens is relatively low. Nanoparticular delivery systems have been applied to improve the immunocompetence of subunit vaccines by targeting lymph nodes, and effectively present antigens to immune cells. Moreover, adding appropriate molecular adjuvants may strengthen the antigens to elicit immune response. In this perspective article, we first elucidate the characteristics of immunity induced by subunit nanovaccines and then summarize the strategies to fabricate subunit nanovaccines with delivering materials. Herein we highlight non-covalent interaction to fabricate nanoparticular subunit vaccines.

The Research Landscape of Multiple Endocrine Neoplasia Type 1 (2000-2021): A Bibliometric Analysis.

Introduction: This study aimed to investigate the landscape of Multiple Endocrine Neoplasia Type 1 research during the last 22 years using machine learning and text analysis. Method: In December 2021, all publications indexed under the MeSH term "Multiple Endocrine Neoplasia Type 1" were obtained from PubMed. The whole set of search results was downloaded in XML format, and metadata such as title, abstract, keywords, mesh words, and year of publication were extracted from the original XML files for bibliometric evaluation. The Latent Dirichlet allocation (LDA) topic modeling method was used to analyze specific themes. Results: This study eventually contained 1,407 publications. Among them, there are 768 (54.58%) case reports and reviews. Text analysis based on MeSH words revealed that the most often studied clinical areas include therapy efficacy, prognosis, and genetic diagnosis. The majority of basic study is focused on genetic alterations. The LDA topic model further identifies three topic clusters include basic research, treatment cluster, and diagnosis cluster. In the basic research cluster, many studies are focused on the expression of Menin. The primary focus of the therapy cluster is pancreatic resections and parathyroidectomy. In the diagnose cluster, the main focus is on Genetic Diagnosis and screening strategies for Hereditary Cancer Syndrome. Conclusion: The current state of research on MEN1 is far from adequate. Research on rare diseases MEN1 necessitates implementing a broad research program involving multiple centers to advance MEN1 research together.

Deep learning-based automatic segmentation of meningioma from multiparametric MRI for preoperative meningioma differentiation using radiomic features: a multicentre study.

OBJECTIVES: Develop and evaluate a deep learning-based automatic meningioma segmentation method for preoperative meningioma differentiation using radiomic features. METHODS: A retrospective multicentre inclusion of MR examinations (T1/T2-weighted and contrast-enhanced T1-weighted imaging) was conducted. Data from centre 1 were allocated to training (n = 307, age = 50.94 ± 11.51) and internal testing (n = 238, age = 50.70 ± 12.72) cohorts, and data from centre 2 external testing cohort (n = 64, age = 48.45 ± 13.59). A modified attention U-Net was trained for meningioma segmentation. Segmentation accuracy was evaluated by five quantitative metrics. The agreement between radiomic features from manual and automatic segmentations was assessed using intra class correlation coefficient (ICC). After univariate and minimum-redundancy-maximum-relevance feature selection, L1-regularized logistic regression models for differentiating between low-grade (I) and high-grade (II and III) meningiomas were separately constructed using manual and automatic segmentations; their performances were evaluated using ROC analysis. RESULTS: Dice of meningioma segmentation for the internal testing cohort were 0.94 ± 0.04 and 0.91 ± 0.05 for tumour volumes in contrast-enhanced T1-weighted and T2-weighted images, respectively; those for the external testing cohort were 0.90 ± 0.07 and 0.88 ± 0.07. Features extracted using manual and automatic segmentations agreed well, for both the internal (ICC = 0.94, interquartile range: 0.88-0.97) and external (ICC = 0.90, interquartile range: 0.78-70.96) testing cohorts. AUC of radiomic model with automatic segmentation was comparable with that of the model with manual segmentation for both the internal (0.95 vs. 0.93, p = 0.176) and external (0.88 vs. 0.91, p = 0.419) testing cohorts. CONCLUSIONS: The developed deep learning-based segmentation method enables automatic and accurate extraction of meningioma from multiparametric MR images and can help deploy radiomics for preoperative meningioma differentiation in clinical practice. KEY POINTS: • A deep learning-based method was developed for automatic segmentation of meningioma from multiparametric MR images. • The automatic segmentation method enabled accurate extraction of meningiomas and yielded radiomic features that were highly consistent with those that were obtained using manual segmentation. • High-grade meningiomas were preoperatively differentiated from low-grade meningiomas using a radiomic model constructed on features from automatic segmentation.