Bufalin-Loaded Multifunctional Photothermal Nanoparticles Inhibit the Anaerobic Glycolysis by Targeting SRC-3/HIF-1α Pathway for Improved Mild Photothermal Therapy in CRC.

Purpose: Compared with traditional photothermal therapy (PTT, >50°C), mild PTT (≤45°C) is a promising strategy for tumor therapy with fewer adverse effects. Unfortunately, its anti-tumor efficacy is hampered by thermoresistance induced by overexpression of heat shock proteins (HSPs). In our previous study, we found bufalin (BU) is a glycolysis inhibitor that depletes HSPs, which is expected to overcome thermotolerance of tumor cells. In this study, BU-loaded multifunctional nanoparticles (NPs) were developed for enhancing the mild PTT of colorectal cancer (CRC). Methods: Fe3O4 NPs coated with the polydopamine (PDA) shell modified with polyethylene glycol (PEG) and cyclic arginine-glycyl-aspartic peptide (cRGD) for loading BU (Fe3O4@PDA-PEG-cRGD/BU NPs) were developed. The thermal variations in Fe3O4@PDA-PEG-cRGD/BU NPs solution under different conditions were measured. Glycolysis inhibition was evaluated by measuring the glucose uptake, extracellular lactate, and intracellular adenosine triphosphate (ATP) levels. The cellular cytotoxicity of Fe3O4@PDA-PEG-cRGD/BU NPs was analyzed using a cell counting kit-8 assay, Calcein-AM/PI double staining, and flow cytometry in HCT116 cells. The magnetic resonance imaging (MRI) performance and anti-tumor therapeutic efficacy of Fe3O4@PDA-PEG-cRGD/BU NPs were evaluated in HCT116-tumor bearing mice. Results: Fe3O4@PDA-PEG-cRGD/BU NPs had an average diameter of 260.4±3.5 nm, the zeta potential of -23.8±1.6 mV, the drug loading rate of 1.1%, which had good thermal stability, photothermal conversion efficiencies and MRI performance. In addition, the released BU not only killed tumor cells but also interfered with glycolysis by targeting the steroid receptor coactivator 3 (SRC-3)/HIF-1α pathway, preventing intracellular ATP synthesis, and combating HSP-dependent tumor thermoresistance, ultimately strengthening the thermal sensitivity toward mild PTT both in vitro and in vivo. Conclusion: This study provides a highly effective strategy for enhancing the therapeutic effects of mild PTT toward tumors.

Theoretical study on optimizing dipeptidomimetic isocyanonaphthalene chemosensor and the fluorescence mechanism for detecting Hg2.

The excited (S1) state charge distribution characteristics and fluorescence mechanism of fluorescence probes benzyl (6-cyano-2-naphthoyl)-L-valinate (NPI) and benzyl (6-amino-2-naphthoyl)-L-valinate (NPA) have been discussed using density functional theory (DFT) and time-dependent density functional theory (TD-DFT). Further analysis by constructing a torsional potential energy curve (PEC) shows that a well-defined minimum energy conformation is observed when the C-C single bond between the valine benzyl ester and naphthalene ring in NPI rotates. For NPA, the most stable conformation is the naphthalene ring conformation with dihedral angle N2C1C2C3 of -30.60°, whose total energy is 0.17 kcal/mol lower than that of the second most stable conformer. The frontier molecular orbitals (FMOs) demonstrate that NPI exhibits a low degree of charge coupling, and the oscillator intensity is close to zero, indicating that it is not conducive to luminescence. However, in the S1 state, the oscillator strength of NPA is 1.2044, which is a bright state, resulting in the strong emitting. Additionally, fluorescence imaging is favored as a visual observation technique, and Stokes shift is an important physical parameter to measure fluorescence. According to the idea that changing the number and position of functional groups can affect the photophysical properties of fluorescent dyes, o-NPDI, p-NPDI and m-NPDI dyes were newly designed and o-NPDA, p-NPDA, m-NPDA produced after recognition of Hg2+. The spectral performance results show that the newly designed fluorescent dye (p-NPDA) can not only emit in the near infrared region after recognizing Hg2+, but also has a large Stokes shift (236 nm). This indirectly reflects that para-substitution is more conducive to Stokes shift, and has become one of the strategies for fluorescent dye design.

Green space exposure and Chinese residents' physical activity participation: empirical evidence from a health geography perspective.

Background: With continuous efforts made to promote the strategic goals of carbon neutrality and carbon peak, it is crucial to meet the growing and diversified needs of the public for fitness by practicing the concept of green development and promote the combination of national fitness and ecological civilization. Methods: To achieve this purpose, an OLS regression model was applied to estimate the role of green space exposure in Chinese residents' participation in physical activity and its underlying mechanisms, using the microdata from the China General Social Survey (CGSS) data and the Provincial Vegetation Cover Index (NDVI) matched macrostatistical data. Results: The empirical results show that green space exposure significantly increases the probability of residents' physical activity participation, and creating a green environment is conducive to creating a favorable physical activity environment for residents. Also, the core conclusions still hold after the year-by-year regression test is passed and the endogeneity problem is addressed. As revealed by mechanistic studies, green space exposure has indirect effects on the physical activity participation of residents through the independent mediating roles of reducing carbon emissions and promoting social interaction. According to heterogeneity results, males, those in marriage, and urban dweller groups are more inclined to perform physical activity in green spaces. Conclusion: The results show that the exposure of green space can help increase the probability of residents' participation in physical exercise, and can that it achieved through two channels: reducing carbon emissions and enhancing social interaction. It is necessary to further strengthen the protection of the ecological lifestyle, give full play to the advantages of greenness and low-carbon, and create favorable conditions for the green development of a new model of national fitness.

High accuracy model for HBsAg loss based on longitudinal trajectories of serum qHBsAg throughout long-term antiviral therapy.

OBJECTIVE: Hepatitis B surface antigen (HBsAg) loss is the optimal outcome for patients with chronic hepatitis B (CHB) but this rarely occurs with currently approved therapies. We aimed to develop and validate a prognostic model for HBsAg loss on treatment using longitudinal data from a large, prospectively followed, nationwide cohort. DESIGN: CHB patients receiving nucleos(t)ide analogues as antiviral treatment were enrolled from 50 centres in China. Quantitative HBsAg (qHBsAg) testing was prospectively performed biannually per protocol. Longitudinal discriminant analysis algorithm was used to estimate the incidence of HBsAg loss, by integrating clinical data of each patient collected during follow-up. RESULTS: In total, 6792 CHB patients who had initiated antiviral treatment 41.3 (IQR 7.6-107.6) months before enrolment and had median qHBsAg 2.9 (IQR 2.3-3.3) log10IU/mL at entry were analysed. With a median follow-up of 65.6 (IQR 51.5-84.7) months, the 5-year cumulative incidence of HBsAg loss was 2.4%. A prediction model integrating all qHBsAg values of each patient during follow-up, designated GOLDEN model, was developed and validated. The AUCs of GOLDEN model were 0.981 (95% CI 0.974 to 0.987) and 0.979 (95% CI 0.974 to 0.983) in the training and external validation sets, respectively, and were significantly better than those of a single qHBsAg measurement. GOLDEN model identified 8.5%-10.4% of patients with a high probability of HBsAg loss (5-year cumulative incidence: 17.0%-29.1%) and was able to exclude 89.6%-91.5% of patients whose incidence of HBsAg loss is 0. Moreover, the GOLDEN model consistently showed excellent performance among various subgroups. CONCLUSION: The novel GOLDEN model, based on longitudinal qHBsAg data, accurately predicts HBsAg clearance, provides reliable estimates of functional hepatitis B virus (HBV) cure and may have the potential to stratify different subsets of patients for novel anti-HBV therapies.

The association between diabetes mellitus and prostate cancer: a meta-analysis and Mendelian randomization.

BACKGROUND: Prostate cancer is one of the most common types of cancer in the US, and it has a high mortality rate. Diabetes mellitus is also a dangerous health condition. While some studies have examined the relationship between diabetes mellitus and the risk of prostate cancer, there is still some debate on the matter. This study aims to carefully assess the relationship between prostate cancer and diabetes from both real-world and genetic-level data. METHODS: This meta-analysis was conducted following the PRISMA 2020 reporting guidelines. The study searched three databases including Medline, Embase and Cochrane. The studies about the incidence risk of prostate cancer with diabetes mellitus were included and used to evaluate the association. The odds ratio (OR), risk ratio (RR) and 95% confidence intervals (95% CI) were estimated using Random Effects models and Fixed Effects models. Mendelian randomization study using genetic variants was also conducted. RESULTS: A total of 72 articles were included in this study. The results showed that risk of prostate cancer decreased in diabetes patients. And the influence was different in different regions. This study also estimated the impact of body mass index (BMI) in the diabetes populations and found that the risk decreased in higher BMI populations. The MR analysis found that diabetes mellitus exposure reduced the risk of prostate cancer in the European population and Asia populations. Conclusions The diabetes mellitus has a protective effect on prostate cancer. And the influence of obesity in diabetes mellitus plays an important role in this effect.

Wnt/ß-catenin signaling in the development and therapeutic resistance of non-small cell lung cancer.

Wnt/ß-catenin signaling is a critical pathway that influences development and therapeutic response of non-small cell lung cancer (NSCLC). In recent years, many Wnt regulators, including proteins, miRNAs, lncRNAs, and circRNAs, have been found to promote or inhibit signaling by acting on Wnt proteins, receptors, signal transducers and transcriptional effectors. The identification of these regulators and their underlying molecular mechanisms provides important implications for how to target this pathway therapeutically. In this review, we summarize recent studies of Wnt regulators in the development and therapeutic response of NSCLC.

Co-evolution of vaginal microbiome and cervical cancer.

BACKGROUND: Exploration of adaptive evolutionary changes at the genetic level in vaginal microbial communities during different stages of cervical cancer remains limited. This study aimed to elucidate the mutational profile of the vaginal microbiota throughout the progression of cervical disease and subsequently establish diagnostic models. METHODS: This study utilized a metagenomic dataset consisting of 151 subjects classified into four categories: invasive cervical cancer (CC) (n = 42), cervical intraepithelial neoplasia (CIN) (n = 43), HPV-infected (HPVi) patients without cervical lesions (n = 34), and healthy controls (n = 32). The analysis focused on changes in microbiome abundance and extracted information on genetic variation. Consequently, comprehensive multimodal microbial signatures associated with CC, encompassing taxonomic alterations, mutation signatures, and enriched metabolic functional pathways, were identified. Diagnostic models for predicting CC were established considering gene characteristics based on single nucleotide variants (SNVs). RESULTS: In this study, we screened and analyzed the abundances of 18 key microbial strains during CC progression. Additionally, 71,6358 non-redundant mutations were identified, predominantly consisting of SNVs that were further annotated into 25,773 genes. Altered abundances of SNVs and mutation types were observed across the four groups. Specifically, there were 9847 SNVs in the HPV-infected group and 14,892 in the CC group. Furthermore, two distinct mutation signatures corresponding to the benign and malignant groups were identified. The enriched metabolic pathways showed limited similarity with only two overlapping pathways among the four groups. HPVi patients exhibited active nucleotide biosynthesis, whereas patients with CC demonstrated a significantly higher abundance of signaling and cellular-associated protein families. In contrast, healthy controls showed a distinct enrichment in sugar metabolism. Moreover, biomarkers based on microbial SNV abundance displayed stronger diagnostic capability (cc.AUC = 0.87) than the species-level biomarkers (cc.AUC = 0.78). Ultimately, the integration of multimodal biomarkers demonstrated optimal performance for accurately identifying different cervical statuses (cc.AUC = 0.86), with an acceptable performance (AUC = 0.79) in the external testing set. CONCLUSIONS: The vaginal microbiome exhibits specific SNV evolution in conjunction with the progression of CC, and serves as a specific biomarker for distinguishing between different statuses of cervical disease.

Prognostic factors in postoperative patients with cutaneous melanoma: a systematic review and meta-analysis.

Cutaneous melanoma is a prevalent tumor associated with a poor prognosis. This systematic review and meta-analysis aimed to identify and evaluate prognostic factors for patients with cutaneous melanoma following surgery, thereby providing crucial insights for enhancing patient outcomes. We searched PubMed, Embase, Cochrane Library, CINAHL, and Web of Science for studies on postoperative prognostic factors of cutaneous melanoma up to March 2024. Literature screening, data extraction, and quality assessment were performed, followed by meta-analysis using RevMan 5.3 software. Trial Sequential Analysis (TSA) was conducted with Stata 17 software to verify the robustness of the findings. Eleven studies encompassing 27,352 patients were included. The meta-analysis identified several prognostic factors impacting disease-specific survival post-surgery: age over 50 years (HR=1.05, 95% CI: 1.02-1.08), female gender (HR=0.71, 95% CI: 0.57-0.87), Breslow thickness greater than 2 mm (HR=1.11, 95% CI: 1.06-1.17), presence of ulceration (HR=2.06, 95% CI: 1.63-2.60), and positive sentinel lymph node (HR=3.03, 95% CI: 2.50-3.66). TSA confirmed the adequacy of the sample size. Aggressive treatment strategies are recommended for patients exhibiting these characteristics to improve prognosis and extend 5-year survival rates.

Genome-Wide Identification and Multi-Stress Response Analysis of the DABB-Type Protein-Encoding Genes in Brassica napus.

The DABB proteins, which are characterized by stress-responsive dimeric A/B barrel domains, have multiple functions in plant biology. In Arabidopsis thaliana, these proteins play a crucial role in defending against various pathogenic fungi. However, the specific roles of DABB proteins in Brassica napus remain elusive. In this study, 16 DABB encoding genes were identified, distributed across 10 chromosomes of the B. napus genome, which were classified into 5 branches based on phylogenetic analysis. Genes within the same branch exhibited similar structural domains, conserved motifs, and three-dimensional structures, indicative of the conservation of BnaDABB genes (BnaDABBs). Furthermore, the enrichment of numerous cis-acting elements in hormone induction and light response were revealed in the promoters of BnaDABBs. Expression pattern analysis demonstrated the involvement of BnaDABBs, not only in the organ development of B. napus but also in response to abiotic stresses and Sclerotinia sclerotiorum infection. Altogether, these findings imply the significant impacts of BnaDABBs on plant growth and development, as well as stress responses.

Neuroprotective effects of Anshen Bunao Syrup on cognitive dysfunction in Alzheimer's disease rat models.

Alzheimer's disease (AD) presents a significant challenge due to its prevalence and lack of cure, driving the quest for effective treatments. Anshen Bunao Syrup, a traditional Chinese medicine known for its neuroprotective properties, shows promise in addressing this need. However, understanding its precise mechanisms in AD remains elusive. This study aimed to investigate Anshen Bunao Syrup's therapeutic potential in AD treatment using a scopolamine-induced AD rat model. Assessments included novel-object recognition and Morris water maze tasks to evaluate spatial learning and memory, alongside Nissl staining and ELISA analyses for neuronal damage and biomarker levels. Results demonstrated that Anshen Bunao Syrup effectively mitigated cognitive dysfunction by inhibiting amyloid-ß and phosphorylation Tau aggregation, thereby reducing neuronal damage. Metabolomics profiling of rats cortex revealed alterations in key metabolites implicated in tryptophan and fatty acid metabolism pathways, suggesting a role in the therapeutic effects of Anshen Bunao Syrup. Additionally, ELISA and correlation analyses indicated attenuation of oxidative stress and immune response through metabolic remodeling. In conclusion, this study provides compelling evidence for the neuroprotective effects of Anshen Bunao Syrup in AD models, shedding light on its potential as a therapeutic agent for AD prevention and treatment.

A new perspective on prostate cancer treatment: the interplay between cellular senescence and treatment resistance.

The emergence of resistance to prostate cancer (PCa) treatment, particularly to androgen deprivation therapy (ADT), has posed a significant challenge in the field of PCa management. Among the therapeutic options for PCa, radiotherapy, chemotherapy, and hormone therapy are commonly used modalities. However, these therapeutic approaches, while inducing apoptosis in tumor cells, may also trigger stress-induced premature senescence (SIPS). Cellular senescence, an entropy-driven transition from an ordered to a disordered state, ultimately leading to cell growth arrest, exhibits a dual role in PCa treatment. On one hand, senescent tumor cells may withdraw from the cell cycle, thereby reducing tumor growth rate and exerting a positive effect on treatment. On the other hand, senescent tumor cells may secrete a plethora of cytokines, growth factors and proteases that can affect neighboring tumor cells, thereby exerting a negative impact on treatment. This review explores how radiotherapy, chemotherapy, and hormone therapy trigger SIPS and the nuanced impact of senescent tumor cells on PCa treatment. Additionally, we aim to identify novel therapeutic strategies to overcome resistance in PCa treatment, thereby enhancing patient outcomes.

MDSCs in bone metastasis: Mechanisms and therapeutic potential.

Bone metastasis (BM) is a frequent complication associated with advanced cancer that significantly increases patient mortality. Myeloid-derived suppressor cells (MDSCs) play a pivotal role in BM progression by promoting angiogenesis, inhibiting immune responses, and inducing osteoclastogenesis. MDSCs induce immunosuppression through diverse mechanisms, including the generation of reactive oxygen species, nitric oxide, and immunosuppressive cytokines. Within the bone metastasis niche (BMN), MDSCs engage in intricate interactions with tumor, stromal, and bone cells, thereby establishing a complex regulatory network. The biological activities and functions of MDSCs are regulated by the microenvironment within BMN. Conversely, MDSCs actively contribute to microenvironmental regulation, thereby promoting BM development. A comprehensive understanding of the indispensable role played by MDSCs in BM is imperative for the development of novel therapeutic strategies. This review highlights the involvement of MDSCs in BM development, their regulatory mechanisms, and their potential as viable therapeutic targets.

Application of machine learning in the study of cobalt-based oxide catalysts for antibiotic degradation: An innovative reverse synthesis strategy.

This study addresses antibiotic pollution in global water bodies by integrating machine learning and optimization algorithms to develop a novel reverse synthesis strategy for inorganic catalysts. We meticulously analyzed data from 96 studies, ensuring quality through preprocessing steps. Employing the AdaBoost model, we achieved 90.57% accuracy in classification and an R²value of 0.93 in regression, showcasing strong predictive power. A key innovation is the Sparrow Search Algorithm (SSA), which optimizes catalyst selection and experimental setup tailored to specific antibiotics. Empirical experiments validated SSA's efficacy, with degradation rates of 94% for Levofloxacin and 97% for Norfloxacin, aligning closely with predictions within a 2% margin of error. This research advances theoretical understanding and offers practical applications in material science and environmental engineering, significantly enhancing catalyst design efficiency and accuracy through the fusion of advanced machine learning techniques and optimization algorithms.

Enhanced cellular therapy: revolutionizing adoptive cellular therapy.

Enhanced cellular therapy has emerged as a novel concept following the basis of cellular therapy. This treatment modality applied drugs or biotechnology to directly enhance or genetically modify cells to enhance the efficacy of adoptive cellular therapy (ACT). Drugs or biotechnology that enhance the killing ability of immune cells include immune checkpoint inhibitors (ICIs) / antibody drugs, small molecule inhibitors, immunomodulatory factors, proteolysis targeting chimera (PROTAC), oncolytic virus (OV), etc. Firstly, overcoming the inhibitory tumor microenvironment (TME) can enhance the efficacy of ACT, which can be achieved by blocking the immune checkpoint. Secondly, cytokines or cytokine receptors can be expressed by genetic engineering or added directly to adoptive cells to enhance the migration and infiltration of adoptive cells to tumor cells. Moreover, multi-antigen chimeric antigen receptors (CARs) can be designed to enhance the specific recognition of tumor cell-related antigens, and OVs can also stimulate antigen release. In addition to inserting suicide genes into adoptive cells, PROTAC technology can be used as a safety switch or degradation agent of immunosuppressive factors to enhance the safety and efficacy of adoptive cells. This article comprehensively summarizes the mechanism, current situation, and clinical application of enhanced cellular therapy, describing potential improvements to adoptive cellular therapy.

In-situ texturing hollow carbon host anchored with Fe single atoms accelerating solid-phase redox for Li-Se batteries.

Se-based cathodes have caught tremendous attention owing to their comparable volumetric capacity and better electronic conductivity to S cathodes. However, its low utilization ratio and sluggish redox kinetics due to the high reaction barrier of solid-phase transformation from Se to Li2Se limit its practical application. Herein, an in-situ texturing hollow carbon host by gas-solid interface reaction anchored with Fe single-atomic catalyst is designed and prepared for advanced Li-Se batteries. This Se host presents high pore volume of 1.49 cm3 g-1, Fe single atom content of 1.53 wt%, and its specific structure protects single-atomic catalyst from the destructive reaction environment, thus balancing catalytic activity and durability. After Se loading by reduction of H2SeO3, this homogenous Se-based cathode delivers a superior rate capacity of 431.3 mA h g-1 at 4C, and great discharge capacity of 301.8 mA h g-1 after 1000 cycles at 10C, with high Li-ion diffusion coefficient and capacitance-contributed ratio. The distribution of relaxation times analysis verifies solid-phase transformation mechanism of this cathode and density functional theory calculations confirm the adsorption and bidirectionally catalysis effect of Fe single-atomic catalyst. This work provides a new strategy to prepare high-efficient Se cathode associated with non-noble metal single atoms for high-performance Li-Se batteries.

Knowledge mapping of application of image-guided surgery in prostate cancer: a bibliometric analysis (2013-2023).

BACKGROUND: Image-guided surgery (IGS) refers to surgery navigated by medical imaging technology, helping doctors better clarify tumor boundaries, identify metastatic lymph nodes and preserve surrounding healthy tissue function. Recent studies have provided expectable momentum of the application of IGS in prostate cancer (PCa). The authors aim to comprehensively construct a bibliometric analysis of the application of IGS in PCa. METHOD: The authors searched publications related to application of IGS in PCa from 2013 to 2023 on the web of science core collection (WoSCC) databases. VOSviewer, CiteSpace, and R package 'bibliometrix' were used for bibliometric analysis. RESULTS: Two thousand three eighty-nine articles from 75 countries and 2883 institutions led by the United States were included. The number of publications related to the application of IGS in PCa kept high in the last decade. Johns Hopkins University is the top research institutions. Journal of Nuclear Medicine has the highest popularity as the selection of journal and co-cited journal. Pomper Martin G. had published the most paper. Ali Afshar-Oromieh was co-cited most frequently. The clinical efficacy of PSMA-PET/CT in PCa diagnosis and treatment are main topics in this research field, with emerging focuses on the use of fluorescence imaging guidance technology in PCa. 'PSMA' and 'PET/CT' are the main keywords as long-term research hotspots. CONCLUSION: This study is the first bibliometric analysis of researches on application of IGS in PCa with three recognized bibliometric software, providing an objective description and comprehensive guidance for the future relevant investigations.

Theoretical investigation on regulating photophysical properties and proton transfer behavior by electronegativity for near-infrared emitting styryl dyes.

Our main focus is to explore the atomic electronegativity-dependent photoinduced behavior of styryl derivatives (HBO, HBS, and HBSe). The results of structural parameter calculation by the DFT method show that the intramolecular hydrogen bonds of normal and tautomer form are strengthened and weakened, respectively, in an excited state (S1), which is conducive to the excited intramolecular proton transfer (ESIPT) process. The enhancement of excited hydrogen bond is beneficial to the ESIPT process from the aspects of infrared vibration frequency (IR), Mulliken's charge analysis, and density gradient reduction (RDG). Additionally, by determining the bond energy with the band critical point (BCP) parameter, we found that the lower the electronegativity of the atom, the larger the hydrogen bond strength at the excited state and the more likely ESIPT reaction occurs. Meanwhile, the intramolecular H-bonds O-H…N in HBO, HBS, and HBSe are enhanced with the weakened electron-withdrawing capacity of the atom (from O to S and Se). Subsequently, frontier molecular orbital (FMOs) and charge density difference (CDD) analyses essentially revealed that electron redistribution induces the ESIPT process. Low atomic electronegativity exhibits the high chemical activity of the excited state. Furthermore, to demonstrate the electronegativity-dependent ESIPT behavior of the system, we built potential energy curves (PECs) and located the transition states (TS) of proton transfer processes.

Blockchain-secure patient Digital Twin in healthcare using smart contracts.

Modern healthcare has a sharp focus on data aggregation and processing technologies. Consequently, from a data perspective, a patient may be regarded as a timestamped list of medical conditions and their corresponding corrective interventions. Technologies to securely aggregate and access data for individual patients in the quest for precision medicine have led to the adoption of Digital Twins in healthcare. Digital Twins are used in manufacturing and engineering to produce digital models of physical objects that capture the essence of device operation to enable and drive optimization. Thus, a patient's Digital Twin can significantly improve health data sharing. However, creating the Digital Twin from multiple data sources, such as the patient's electronic medical records (EMR) and personal health records (PHR) from wearable devices, presents some risks to the security of the model and the patient. The constituent data for the Digital Twin should be accessible only with permission from relevant entities and thus requires authentication, privacy, and provable provenance. This paper proposes a blockchain-secure patient Digital Twin that relies on smart contracts to automate the updating and communication processes that maintain the Digital Twin. The smart contracts govern the response the Digital Twin provides when queried, based on policies created for each patient. We highlight four research points: access control, interaction, privacy, and security of the Digital Twin and we evaluate the Digital Twin in terms of latency in the network, smart contract execution times, and data storage costs.

Normalizing Flow-Based Distribution Estimation of Pharmacokinetic Parameters in Dynamic Contrast-Enhanced Magnetic Resonance Imaging.

OBJECTIVE: The pharmacokinetic (PK) parameters estimated from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) provide valuable information for clinical research and diagnosis. However, these estimated PK parameters suffer from many sources of variability. Thus, the estimation of the posterior distributions of these PK parameters could provide a way to simultaneously quantify the values and uncertainties of the PK parameters. Our objective is to develop an efficient and flexible method to more closely approximate and estimate the underlying posterior distributions of the PK parameters. METHODS: The normalizing flow model-based parameters distribution estimation neural network (FPDEN) is proposed to adaptively learn and estimate the posterior distributions of the PK parameters. The maximum likelihood estimation (MLE) loss is directly constructed based on the parameter distributions learned by the normalizing flow model, rather than pre-defined distributions. RESULTS: Experimental analysis shows that the proposed method can improve parameter estimation accuracy. Moreover, the uncertainty derived from the parameter distribution constitutes an effective indicator to exclude unreliable parametric results. A successful demonstration is the improved classification performance of the glioma World Health Organization (WHO) grading task, specifically in terms of distinguishing between low and high grades, as well as between Grade III and Grade IV. CONCLUSION: The FPDEN method offers improved accuracy for estimation of PK parameters and boosts the performance of the glioma grading task. SIGNIFICANCE: By enhancing the precision and reliability of DCE-MRI, the proposed method promotes its further applications in clinical practice.