Formaldehyde exacerbates inflammation and biases T helper cell lineage commitment through IFN-γ/STAT1/T-bet pathway in asthma.

The correlation between formaldehyde (FA) exposure and prevalence of asthma has been widely reported. However, the underlying mechanism is still not fully understood. FA exposure at 2.0 mg/m3 was found to exacerbate asthma in OVA-induced murine models. IFN-γ, the cytokine produced by T helper 1 (Th1) cells, was significantly induced by FA in serum and bronchoalveolar lavage fluid (BALF) of asthmatic mice, which was different from cytokines secreted by other Th cells. The observation was also confirmed by mRNA levels of Th marker genes in CD4+ T cells isolated from BALF. In addition, increased production of IFN-γ and expression of T-bet in Jurkat T cells primed with phorbol ester and phytohaemagglutinin were also observed with 100 µM FA treatment in vitro. Upregulated STAT1 phosphorylation, T-bet expression and IFN-γ production induced by FA was found to be restrained by STAT1 inhibitor fludarabine, indicating that FA promoted Th1 commitment through the autocrine IFN-γ/STAT1/T-bet pathway in asthma. This work not only revealed that FA could bias Th lineage commitment to exacerbate allergic asthma, but also identified the signaling mechanism of FA-induced Th1 differentiation, which may be utilized as the target for development of interfering strategies against FA-induced immune disorders.

Enhancement of silicon vacancy fluorescence intensity in silicon carbide using a dielectric cavity.

Over the past decades, spin qubits in silicon carbide (SiC) have emerged as promising platforms for a wide range of quantum technologies. The fluorescence intensity holds significant importance in the performance of quantum photonics, quantum information process, and sensitivity of quantum sensing. In this work, a dual-layer Au/SiO2 dielectric cavity is employed to enhance the fluorescence intensity of a shallow silicon vacancy ensemble in 4H-SiC. Experimental results demonstrate an effective fourfold augmentation in fluorescence counts at saturating laser power, corroborating our theoretical predictions. Based on this, we further investigate the influence of dielectric cavities on the contrast and linewidth of optically detected magnetic resonance (ODMR). There is a 1.6-fold improvement in magnetic field sensitivity. In spin echo experiments, coherence times remain constant regardless of the thickness of dielectric cavities. These experiments pave the way for broader applications of dielectric cavities in SiC-based quantum technologies.

Multi-Component Lithiophilic Alloy Film Modified Cu Current Collector for Long-Life Lithium Metal Batteries by a Novel FCVA Co-Deposition System.

Surface modification of Cu current collectors (CCs) is proven to be an effective method for protecting lithium metal anodes. However, few studies have focused on the quality and efficiency of modification layers. Herein, a novel home-made filtered cathode vacuum arc (FCVA) co-deposition system with high modification efficiency, good repeatability and environmental friendliness is proposed to realize the wide range regulation of film composition, structure and performance. Through this system, ZnMgTiAl quaternary alloy films, which have good affinity with Li are successfully constructed on Cu CCs, and the fully enhanced electrochemical performances are achieved. Symmetrical cells constructed with modified CCs maintained a fairly low voltage hysteresis of only 13 mV after 2100 h at a current density of 1 mA cm-2. In addition, the capacity retention rate is as high as 75.0% after 100 cycles in the full cells. The influence of alloy films on the dynamic evolution process of constructing stable artificial solid electrolyte interphase (SEI) layer is revealed by in situ infrared (IR) spectroscopy. This work provides a promising route for designing various feasible modification films for LMBs, and it displays better industrial application prospects than the traditional chemical methods owing to the remarkable controllability and scale-up capacity.

Leveraging machine learning for predicting acute graft-versus-host disease grades in allogeneic hematopoietic cell transplantation for T-cell prolymphocytic leukaemia.

Orphan diseases, exemplified by T-cell prolymphocytic leukemia, present inherent challenges due to limited data availability and complexities in effective care. This study delves into harnessing the potential of machine learning to enhance care strategies for orphan diseases, specifically focusing on allogeneic hematopoietic cell transplantation (allo-HCT) in T-cell prolymphocytic leukemia. The investigation evaluates how varying numbers of variables impact model performance, considering the rarity of the disease. Utilizing data from the Center for International Blood and Marrow Transplant Research, the study scrutinizes outcomes following allo-HCT for T-cell prolymphocytic leukemia. Diverse machine learning models were developed to forecast acute graft-versus-host disease (aGvHD) occurrence and its distinct grades post-allo-HCT. Assessment of model performance relied on balanced accuracy, F1 score, and ROC AUC metrics. The findings highlight the Linear Discriminant Analysis (LDA) classifier achieving the highest testing balanced accuracy of 0.58 in predicting aGvHD. However, challenges arose in its performance during multi-class classification tasks. While affirming the potential of machine learning in enhancing care for orphan diseases, the study underscores the impact of limited data and disease rarity on model performance.

Biogeography and impact of nitrous oxide reducers in rivers across a broad environmental gradient on emission rates.

Microbial communities that reduce nitrous oxide (N2O) are divided into two clades, nosZI and nosZII. These clades significantly differ in their ecological niches and their implications for N2O emissions in terrestrial environments. However, our understanding of N2O reducers in aquatic systems is currently limited. This study investigated the relative abundance and diversity of nosZI- and nosZII-type N2O reducers in rivers and their impact on N2O emissions. Our findings revealed that stream sediments possess a high capacity for N2O reduction, surpassing N2O production under high N2O/NO3- ratio conditions. This study, along with others in freshwater systems, demonstrated that nosZI marginally dominates more often in rivers. While microbes containing either nosZI and nosZII were crucial in reducing N2O emissions, the net contribution of nosZII-containing microbes was more significant. This can be attributed to the nir gene co-occurring more frequently with the nosZI gene than with the nosZII gene. The diversity within each clade also played a role, with nosZII species being more likely to function as N2O sinks in streams with higher N2O concentrations. Overall, our findings provide a foundation for a better understanding of the biogeography of stream N2O reducers and their effects on N2O emissions.

Metabolism characterization and toxicity of N-hydap, a marine candidate drug for lung cancer therapy by LC-MS method.

N-Hydroxyapiosporamide (N-hydap), a marine product derived from a sponge-associated fungus, has shown promising inhibitory effects on small cell lung cancer (SCLC). However, there is limited understanding of its metabolic pathways and characteristics. This study explored the in vitro metabolic profiles of N-hydap in human recombinant cytochrome P450s (CYPs) and UDP-glucuronosyltransferases (UGTs), as well as human/rat/mice microsomes, and also the pharmacokinetic properties by HPLC-MS/MS. Additionally, the cocktail probe method was used to investigate the potential to create drug-drug interactions (DDIs). N-Hydap was metabolically unstable in various microsomes after 1 h, with about 50% and 70% of it being eliminated by CYPs and UGTs, respectively. UGT1A3 was the main enzyme involved in glucuronidation (over 80%), making glucuronide the primary metabolite. Despite low bioavailability (0.024%), N-hydap exhibited a higher distribution in the lungs (26.26%), accounting for its efficacy against SCLC. Administering N-hydap to mice at normal doses via gavage did not result in significant toxicity. Furthermore, N-hydap was found to affect the catalytic activity of drug metabolic enzymes (DMEs), particularly increasing the activity of UGT1A3, suggesting potential for DDIs. Understanding the metabolic pathways and properties of N-hydap should improve our knowledge of its drug efficacy, toxicity, and potential for DDIs.

Bioaccessibility and human health risks of arsenic from geological origin in lateritic red soil on construction land.

Current human health risk assessments of soil arsenic (As) contamination rarely consider bioaccessibility (IVBA), which may overestimate the health risks of soil As. The IVBA of As (As-IVBA) may differ among various soil types. This investigation of As-IVBA focused As from geological origin in a typical subtropical soil, lateritic red soil, and its risk control values. The study used the SBRC gastric phase in vitro digestion method and As speciation sequential extraction based upon phosphorus speciation extraction method. Two construction land sites (CH and HD sites) in the Pearl River Delta region were surveyed. The results revealed a high content of residual As (including scorodite, mansfieldite, orpiment, realgar, and aluminum arsenite) in the lateritic red soils at both sites (CH: 84.9%, HD: 91.7%). The content of adsorbed aluminum arsenate (CH: 3.24%, HD: 0.228%), adsorbed ferrum arsenate (CH: 8.55%, HD: 5.01%), and calcium arsenate (CH: 7.33%, HD: 3.01%) were found to be low. The bioaccessible As content was significantly positively correlated with the As content in adsorbed aluminum arsenate, adsorbed ferrum arsenate, and calcium arsenate. A small portion of these sequential extractable As speciation could be absorbed by the human body (CH: 14.9%, HD: 3.16%), posing a certain health risk. Adsorbed aluminum arsenate had the highest IVBA, followed by calcium arsenate, and adsorbed ferrum arsenate had the lowest IVBA. The aforementioned speciation characteristics of As from geological origin in lateritic red soil contributed to its lower IVBA compared to other soils. The oxidation state of As did not significantly affect As-IVBA. Based on As-IVBA, the carcinogenic and non-carcinogenic risks of soil As in the CH and HD sites decreased greatly in human health risk assessment. The results suggest that As-IVBA in lateritic red soil should be considered when assessing human health risks on construction land.

Myricetin Acts as an Inhibitor of Type II NADH Dehydrogenase from Staphylococcus aureus.

BACKGROUND: Staphylococcus aureus is a common pathogenic microorganism in humans and animals. Type II NADH oxidoreductase (NDH-2) is the only NADH:quinone oxidoreductase present in this organism and represents a promising target for the development of anti-staphylococcal drugs. Recently, myricetin, a natural flavonoid from vegetables and fruits, was found to be a potential inhibitor of NDH-2 of S. aureus. The objective of this study was to evaluate the inhibitory properties of myricetin against NDH-2 and its impact on the growth and expression of virulence factors in S. aureus. RESULTS: A screening method was established to identify effective inhibitors of NDH-2, based on heterologously expressed S. aureus NDH-2. Myricetin was found to be an effective inhibitor of NDH-2 with a half maximal inhibitory concentration (IC50) of 2 µM. In silico predictions and enzyme inhibition kinetics further characterized myricetin as a competitive inhibitor of NDH-2 with respect to the substrate menadione (MK). The minimum inhibitory concentrations (MICs) of myricetin against S. aureus strains ranged from 64 to 128 µg/mL. Time-kill assays showed that myricetin was a bactericidal agent against S. aureus. In line with being a competitive inhibitor of the NDH-2 substrate MK, the anti-staphylococcal activity of myricetin was antagonized by MK-4. In addition, myricetin was found to inhibit the gene expression of enterotoxin SeA and reduce the hemolytic activity induced by S. aureus culture on rabbit erythrocytes in a dose-dependent manner. CONCLUSIONS: Myricetin was newly discovered to be a competitive inhibitor of S. aureus NDH-2 in relation to the substrate MK. This discovery offers a fresh perspective on the anti-staphylococcal activity of myricetin.

Crosstalk between T lymphocyte and extracellular matrix in tumor microenvironment.

The extracellular matrix (ECM) is a complex three-dimensional structure composed of proteins, glycans, and proteoglycans, constituting a critical component of the tumor microenvironment. Complex interactions among immune cells, extracellular matrix, and tumor cells promote tumor development and metastasis, consequently influencing therapeutic efficacy. Hence, elucidating these interaction mechanisms is pivotal for precision cancer therapy. T lymphocytes are an important component of the immune system, exerting direct anti-tumor effects by attacking tumor cells or releasing lymphokines to enhance immune effects. The ECM significantly influences T cells function and infiltration within the tumor microenvironment, thereby impacting the behavior and biological characteristics of tumor cells. T cells are involved in regulating the synthesis, degradation, and remodeling of the extracellular matrix through the secretion of cytokines and enzymes. As a result, it affects the proliferation and invasive ability of tumor cells as well as the efficacy of immunotherapy. This review discusses the mechanisms underlying T lymphocyte-ECM interactions in the tumor immune microenvironment and their potential application in immunotherapy. It provides novel insights for the development of innovative tumor therapeutic strategies and drug.

Unexpected Intermolecular C-H···O Hydrogen Bonds and 1H NMR Chemical Shifts in a Key Linker for Fluorine-18 Labeling of Dimeric Drugs.

The compound 2-{[(trifluoromethyl)sulfonyl]oxy}propane-1,3-diyl bis(4-methylbenzenesulfonate) (TPB) is a crucial intermediate in the synthesis of 18F-radiolabeled cromolyn derivatives. In this work, we combine 1H NMR spectroscopy, X-ray crystallography, ab initio molecular dynamics, and NMR calculations to examine the structure, interactions, and solvation dynamics of the TPB molecule. In CDCl3, the CH2 groups within its glyceryl-derived linker exhibit a single set of proton signals in the 1H NMR measurements. However, when TPB is dissolved in DMSO-d6, distinct splitting patterns emerge despite its seemingly symmetric chemical structure. Crystallographic analysis further unveils the absence of overall symmetry in its three-dimensional arrangement. To elucidate these unique NMR features, we carry out ab initio molecular dynamics simulations and characterize the solvation structures and dynamics of TPB in CHCl3 and DMSO solutions. In contrast to the predominantly nonpolar nature of the CHCl3 solvents, DMSO directly participates in C-H···O hydrogen-bonding interactions with the solute molecule, leading to the splitting of its -CH2 chemical shifts into two distinct distributions. The comprehensive understanding of the structure and solvation interactions of TPB provides essential insights into its application in the radiofluorination reactions of cromolyn derivatives and holds promise for the future development of radiolabeled dimeric drugs.

Neuroprotective azaphilones from a deep-sea derived fungus Penicillium sp. SCSIO41030.

Ten azaphilones including one pair of new epimers and three new ones, penineulones A-E (1-5) with the same structural core of angular deflectin, were obtained from a deep-sea derived Penicillium sp. SCSIO41030 fermented on a liquid medium. Their structures including absolute configurations were elucidated using chiral-phase HPLC analysis, extensive NMR spectroscopic and HRESIMS data, ECD and NMR calculations, and by comparing NMR data with literature data. Biological assays showed that the azaphilones possessed no antitumor and anti-viral (HSV-1/2) activities at concentrations of 5.0 µM and 20 µM, respectively. In addition, azaphilones 8 and 9 showed neuroprotective effects against Aß25-35-induced neurotoxicity in primary cultured cortical neurons at a concentration of 10 µM. Azaphilones 8 and 9 dramatically promoted axonal regrowth against Aß25-35-induced axonal atrophy. Our study indicated that azaphilones could be promising lead compounds for neuroprotection.

Recent advances in total synthesis of protoberberine and chiral tetrahydroberberine alkaloids.

Covering: Up to 2024Due to the widespread distribution of protoberberine alkaloids (PBs) and tetrahydroberberine alkaloids (THPBs) in nature, coupled with their myriad unique physiological activities, they have garnered considerable attention from medical practitioners. Over the past few decades, synthetic chemists have devised various total synthesis methods to attain these structures, continually expanding reaction pathways to achieve more efficient synthetic strategies. Simultaneously, the chiral construction of THPBs has become a focal point. In this comprehensive review, we categorically summarized the developmental trajectory of the total synthesis of these alkaloids based on the core closure strategies of protoberberine and tetrahydroberberine.

Immunomodulation of adipose-derived mesenchymal stem cells on peripheral blood mononuclear cells in colorectal cancer patients with COVID-19.

BACKGROUND: Accumulating evidence has shown that adipose tissue-derived mesenchymal stem cells (ADSCs) are an effective therapeutic approach for managing coronavirus disease 2019 (COVID-19); however, further elucidation is required to determine their underlying immunomodulatory effect on the mRNA expression of T helper cell-related transcription factors (TFs) and cytokine release in peripheral blood mononuclear cells (PBMCs). AIM: To investigate the impact of ADSCs on the mRNA expression of TFs and cytokine release in PBMCs from colorectal cancer (CRC) patients with severe COVID-19 (CRC+ patients). METHODS: PBMCs from CRC+ patients (PBMCs-C+) and age-matched CRC patients (PBMCs-C) were stimulated and cultured in the presence/absence of ADSCs. The mRNA levels of T-box TF TBX21 (T-bet), GATA binding protein 3 (GATA-3), RAR-related orphan receptor C (RORC), and forkhead box P3 (FoxP3) in the PBMCs were determined by reverse transcriptase-polymerase chain reaction. Culture supernatants were evaluated for levels of interferon gamma (IFN-γ), interleukin 4 (IL-4), IL-17A, and transforming growth factor beta 1 (TGF-ß1) using an enzyme-linked immunosorbent assay. RESULTS: Compared with PBMCs-C, PBMCs-C+ exhibited higher mRNA levels of T-bet and RORC, and increased levels of IFN-γ and IL-17A. Additionally, a significant decrease in FoxP3 mRNA and TGF-ß1, as well as an increase in T-bet/GATA-3, RORC/FoxP3, IFN-γ/IL-4, and IL-17A/TGF-ß1 ratios were observed in PBMCs-C+. Furthermore, ADSCs significantly induced a functional regulatory T cell (Treg) subset, as evidenced by an increase in FoxP3 mRNA and TGF-ß1 release levels. This was accompanied by a significant decrease in the mRNA levels of T-bet and RORC, release of IFN-γ and IL-17A, and T-bet/GATA-3, RORC/FoxP3, IFN-γ/IL-4, and IL-17A/TGF-ß1 ratios, compared with the PBMCs-C+alone. CONCLUSION: The present in vitro studies showed that ADSCs contributed to the immunosuppressive effects on PBMCs-C+, favoring Treg responses. Thus, ADSC-based cell therapy could be a beneficial approach for patients with severe COVID-19 who fail to respond to conventional therapies.

Consolidated Health Economic Evaluation Reporting Standards for Interventions that use Artificial Intelligence (CHEERS-AI).

OBJECTIVES: Economic evaluations (EEs) are commonly used by decision makers to understand the value of health interventions. The Consolidated Health Economic Evaluation Reporting Standards (CHEERS 2022) provide reporting guidelines for EEs. Healthcare systems will increasingly see new interventions that use artificial intelligence (AI) to perform their function. We developed CHEERS-AI to ensure EEs of AI-based health interventions are reported in a transparent and reproducible manner. METHODS: Potential CHEERS-AI reporting items were informed by 2 published systematic literature reviews of EEs and a contemporary update. A Delphi study was conducted using 3 survey rounds to elicit multidisciplinary expert views on 26 potential items, through a 9-point Likert rating scale and qualitative comments. An online consensus meeting was held to finalise outstanding reporting items. A digital health patient group reviewed the final checklist from a patient perspective. RESULTS: A total of 58 participants responded to survey round 1, 42 and 31 of whom responded to rounds 2 and 3, respectively. Nine participants joined the consensus meeting. Ultimately, 38 reporting items were included in CHEERS-AI. They comprised the 28 original CHEERS 2022 items, plus 10 new AI-specific reporting items. Additionally, 8 of the original CHEERS 2022 items were elaborated on to ensure AI-specific nuance is reported. CONCLUSIONS: CHEERS-AI should be used when reporting an EE of an intervention that uses AI to perform its function. CHEERS-AI will help decision makers and reviewers to understand important AI-specific details of an intervention, and any implications for the EE methods used and cost-effectiveness conclusions.

A Blueprint for Multi-use Disease Modeling in Health Economics: Results from Two Expert-Panel Consultations.

BACKGROUND: The current use of health economic decision models in HTA is mostly confined to single use cases, which may be inefficient and result in little consistency over different treatment comparisons, and consequently inconsistent health policy decisions, for the same disorder. Multi-use disease models (MUDMs) (other terms: generic models, whole disease models, disease models) may offer a solution. However, much is uncertain about their definition and application. The current research aimed to develop a blueprint for the application of MUDMs. METHODS: We elicited expert opinion using a two-round modified Delphi process. The panel consisted of experts and stakeholders in health economic modelling from various professional backgrounds. The first questionnaire concerned definition, terminology, potential applications, issues and recommendations for MUDMs and was based on an exploratory scoping review. In the second round, the panel members were asked to reconsider their input, based on feedback regarding first-round results, and to score issues and recommendations for priority. Finally, adding input from external advisors and policy makers in a structured way, an overview of issues and challenges was developed during two team consensus meetings. RESULTS: In total, 54 respondents contributed to the panel results. The term 'multi-use disease models' was proposed and agreed upon, and a definition was provided. The panel prioritized 10 potential applications (with comparing alternative policies and supporting resource allocation decisions as the top 2), while 20 issues (with model transparency and stakeholders' roles as the top 2) were identified as challenges. Opinions on potential features concerning operationalization of multi-use models were given, with 11 of these subsequently receiving high priority scores (regular updates and revalidation after updates were the top 2). CONCLUSIONS: MUDMs would improve on current decision support regarding cost-effectiveness information. Given feasibility challenges, this would be most relevant for diseases with multiple treatments, large burden of disease and requiring more complex models. The current overview offers policy makers a starting point to organize the development, use, and maintenance of MUDMs and to support choices concerning which diseases and policy decisions they will be helpful for.

Gradient Alloy Shell Enabling Colloidal Quantum Wells Light-Emitting Diodes with Efficiency Exceeding 22.

Colloidal quantum well (CQW) based light emitting diodes (LEDs) possess extra-high theoretical efficiency, but their performance still lags far behind conventional LEDs due to severe exciton quenching and unbalanced charge injection. Herein, we devised a gradient composition CdxZn1-xS shell to address these issues. The epitaxial shell with gradient composition was achieved through controlling competition between Cd2+ and Zn2+ cations to preferentially bind to the anions S2-. Thus, exciton quenching was suppressed greatly by passivating defects and reducing nonradiative recombination, thereby achieving near-unity photoluminescence quantum yield (PLQY). The gradient energy level of the shell reduced the hole injection barriers and increased the hole injection efficiency to balance the charge injection of LEDs. As a result, the LEDs achieved a high external quantum efficiency (EQE) of 22.83%, luminance of 111,319 cd/m2 and a long operational lifetime (T95@100 cd/m2) over 6,500 h, demonstrating the state-of-the-art performance for the CQW based LEDs.

Anti-inflammatory and Neuroprotective α-Pyrones from a Marine-Derived Strain of the Fungus Arthrinium arundinis and Their Heterologous Expression.

Fungal linear polyketides, such as α-pyrones with a 6-alkenyl chain, have been a rich source of biologically active compounds. Two new (1 and 2) and four known (3-6) 6-alkenylpyrone polyketides were isolated from a marine-derived strain of the fungus Arthrinium arundinis. Their structures were determined based on extensive spectroscopic analysis. The biosynthetic gene cluster (alt) for alternapyrones was identified from A. arundinis ZSDS-F3 and validated by heterologous expression in Aspergillus nidulans A1145 ΔSTΔEM, which revealed that the cytochrome P450 monooxygenase Alt2' could convert the methyl group 26-CH3 to a carboxyl group to produce 4 from 3. Another cytochrome P450 monooxygenase, Alt3', catalyzed successive hydroxylation, epoxidation, and oxidation steps to produce 1, 2, 5, and 6 from 4. Alternapyrone G (1) not only suppressed M1 polarization in lipopolysaccharide (LPS)-stimulated BV2 microglia but also stimulated dendrite regeneration and neuronal survival after Aß treatment, suggesting alternapyrone G may be utilized as a privileged scaffold for Alzheimer's disease drug discovery.

Quantum annealing of a frustrated magnet.

Quantum annealing, which involves quantum tunnelling among possible solutions, has state-of-the-art applications not only in quickly finding the lowest-energy configuration of a complex system, but also in quantum computing. Here we report a single-crystal study of the frustrated magnet α-CoV2O6, consisting of a triangular arrangement of ferromagnetic Ising spin chains without evident structural disorder. We observe quantum annealing phenomena resulting from time-reversal symmetry breaking in a tiny transverse field. Below ~ 1 K, the system exhibits no indication of approaching the lowest-energy state for at least 15 hours in zero transverse field, but quickly converges towards that configuration with a nearly temperature-independent relaxation time of ~ 10 seconds in a transverse field of ~ 3.5 mK. Our many-body simulations show qualitative agreement with the experimental results, and suggest that a tiny transverse field can profoundly enhance quantum spin fluctuations, triggering rapid quantum annealing process from topological metastable Kosterlitz-Thouless phases, at low temperatures.

From Coarse to Fine: Non-Rigid Sparse-Dense Registration for Deformation-Aware Liver Surgical Navigation.

OBJECTIVE: Intraoperative liver deformation poses a considerable challenge during liver surgery, causing significant errors in image-guided surgical navigation systems. This study addresses a critical non-rigid registration problem in liver surgery: the alignment of intrahepatic vascular trees. The goal is to deform the complete vascular shape extracted from preoperative Computed Tomography (CT) volume, aligning it with sparse vascular contour points obtained from intraoperative ultrasound (iUS) images. Challenges arise due to the intricate nature of slender vascular branches, causing existing methods to struggle with accuracy and vascular self-intersection. METHODS: We present a novel non-rigid sparse-dense registration pipeline structured in a coarse-to-fine fashion. In the initial coarse registration stage, we introduce a parametrization deformation graph and a Welsch function-based error metric to enhance convergence and robustness of non-rigid registration. For the fine registration stage, we propose an automatic curvature-based algorithm to detect and eliminate overlapping regions. Subsequently, we generate the complete vascular shape using posterior computation of a Gaussian Process Shape Model. RESULTS: Experimental results using simulated data demonstrate the accuracy and robustness of our proposed method. Evaluation results on the target registration error of tumors highlight the clinical significance of our method in tumor location computation. Comparative analysis against related methods reveals superior accuracy and competitive efficiency of our approach. Moreover, Ex vivo swine liver experiments and clinical experiments were conducted to evaluate the method's performance. CONCLUSION: The experimental results itasize the accurate and robust performance of our proposed method. SIGNIFICANCE: Our proposed non-rigid registration method holds significant application potential in clinical practice.

DFUSNN: zero-shot dual-domain fusion unsupervised neural network for parallel MRI reconstruction.

Objective. Recently, deep learning models have been used to reconstruct parallel magnetic resonance (MR) images from undersampled k-space data. However, most existing approaches depend on large databases of fully sampled MR data for training, which can be challenging or sometimes infeasible to acquire in certain scenarios. The goal is to develop an effective alternative for improved reconstruction quality that does not rely on external training datasets.Approach. We introduce a novel zero-shot dual-domain fusion unsupervised neural network (DFUSNN) for parallel MR imaging reconstruction without any external training datasets. We employ the Noise2Noise (N2N) network for the reconstruction in the k-space domain, integrate phase and coil sensitivity smoothness priors into the k-space N2N network, and use an early stopping criterion to prevent overfitting. Additionally, we propose a dual-domain fusion method based on Bayesian optimization to enhance reconstruction quality efficiently.Results. Simulation experiments conducted on three datasets with different undersampling patterns showed that the DFUSNN outperforms all other competing unsupervised methods and the one-shot Hankel-k-space generative model (HKGM). The DFUSNN also achieves comparable results to the supervised Deep-SLR method.Significance. The novel DFUSNN model offers a viable solution for reconstructing high-quality MR images without the need for external training datasets, thereby overcoming a major hurdle in scenarios where acquiring fully sampled MR data is difficult.