Determination of cotinine and 3-hydroxynicotinine in human serum by liquid chromatography-tandem mass spectrometry and its application.

In this study, we developed a method for determining cotinine and 3-hydroxycotinine in human serum and established a methodology for an in-depth study of tobacco exposure and health. After the proteins in the human serum samples were precipitated with acetonitrile, they were separated on a ZORBAX SB-Phenyl column with a mobile phase of methanol encompassing 0.3% formic acid-water encompassing 0.15% formic acid. The measurement was performed on an API5500 triple quadrupole mass spectrometer in the multiple reaction monitoring mode. Cotinine, 3-hydroxycotinine, and cotinine-d3 isotope internal standards were held for 2.56 minutes, 1.58 minutes, and 2.56 minutes, respectively. In serum, the linear range was 0.05 to 500 ng·mL-1 for cotinine and 0.50 to 1250 ng·mL-1 for 3-hydroxycotinine. The lower limit of quantification (LLOQ) was 0.05 ng·mL-1 and 0.5 ng·mL-1 for cotinine and 3-hydroxycotinine, respectively. The intra-day and inter-day relative standard deviations were <11%, and the relative errors were within ±â€…7%. Moreover, the mean extraction recoveries of cotinine and 3-hydroxycotinine were 98.54% and 100.24%, respectively. This method is suitable for the rapid determination of cotinine and 3-hydroxycotinine in human serum because of its rapidity, sensitivity, strong specificity, and high reproducibility. The detection of cotinine levels in human serum allows for the identification of the cutoff value, providing a basis for differentiation between smoking and nonsmoking populations.

Unraveling the role of sulfiredoxin-1 in early-onset preeclampsia: A key player in trophoblast ferroptosis.

Preeclampsia (PE) significantly contributes to obstetric complications and maternal mortality, yet its pathogenesis and mechanisms are not well understood. Sulfiredoxin-1 (SRXN1) is known for its antioxidant activity and its role in defending against oxidative stress; it is also linked to various cancers. However, the role of SRXN1 in PE remains unclear. Our study found a significant decrease in SRXN1 levels in the serum and placental tissues of patients with early-onset preeclampsia (EOPE). Similarly, a PE-like mouse model showed reduced SRXN1 expression. Our in vitro experiments showed that reducing SRXN1 impaired trophoblast viability, decreased invasion and migration, and led to cell death, primarily through ferroptosis. These results are consistent with analyses of placental tissues from EOPE patients. In summary, lower SRXN1 levels during pregnancy contribute to trophoblast ferroptosis, potentially affecting the development and progression of EOPE.

A preliminary investigation of precise visualization, localization, and resection of pelvic lymph nodes in bladder cancer by using indocyanine green fluorescence-guided approach through intracutaneous dye injection into the lower limbs and perineum.

Objective: This study aimed to investigate the feasibility and effectiveness of using indocyanine green (ICG) injected intracutaneously through the lower limbs and perineum for visualized tracking, localization, and qualitative assessment of pelvic lymph nodes (LNs) in bladder cancer to achieve their accurate resection. Methods: First, ICG was injected into the LN metastasis model mice lower limbs, and real-time and dynamic in vivo and ex vivo imaging was conducted by using a near-infrared fluorescence imaging system. Additionally, 26 patients with bladder cancer were enrolled and divided into intracutaneous group and transurethral group. A near-infrared fluorescence imaging device with internal and external imaging probes was used to perform real-time tracking, localization, and resection of the pelvic LNs. Results: The mice normal LNs and the metastatic LNs exhibited fluorescence. The metastatic LNs showed a significantly higher signal-to-background ratio than the normal LNs (3.9 ± 0.2 vs. 2.0 ± 0.1, p < 0.05). In the intracutaneous group, the accuracy rate of fluorescent-labeled LNs was 97.6%, with an average of 11.3 ± 2.4 LNs resected per patient. Six positive LNs were detected in three patients (18.8%). In the transurethral group, the accuracy rate of fluorescent-labeled LNs was 84.4%, with an average of 8.6 ± 2.3 LNs resected per patient. Two positive LNs were detected in one patient (12.5%). Conclusion: Following the intracutaneous injection of ICG into the lower limbs and perineum, the dye accumulates in pelvic LNs through lymphatic reflux. By using near-infrared fluorescence laparoscopic fusion imaging, physicians can perform real-time tracking, localization, and precise resection of pelvic LNs.

A novel transcription and replication-competent virus-like particles system modelling the Nipah virus life cycle.

AbstractNipah virus (NiV), a highly pathogenic Henipavirus in humans, has been responsible for annual outbreaks in recent years. Experiments revolving live NiV are highly restricted to biosafety level 4 (BSL-4) laboratories, which impedes NiV research. In this study, we developed a transcription and replication-competent NiV-like particles (trVLP-NiV) lacking N, P, and L genes. This trVLP-NiV exhibited the ability to infect and continuously passage in cells ectopically expressing N, P, and L proteins while maintaining stable genetic characteristics. Moreover, the trVLP-NiV displayed a favourable safety profile in hamsters. Using the system, we found the NiV nucleoprotein residues interacting with viral RNA backbone affected viral replication in opposite patterns. This engineered system was sensitive to well-established antiviral drugs, innate host antiviral factors, and neutralising antibodies. We then established a high-throughput screening platform utilizing the trVLP-NiV, leading to the identification of tunicamycin as a potential anti-NiV compound. Evidence showed that tunicamycin inhibited NiV replication by decreasing the infectivity of progeny virions. In conclusion, this trVLP-NiV system provided a convenient and versatile molecular tool for investigating NiV molecular biology and conducting antiviral drug screening under BSL-2 conditions. Its application will contribute to the development of medical countermeasures against NiV infections.

Image-domain material decomposition for dual-energy CT using unsupervised learning with data-fidelity loss.

BACKGROUND: Dual-energy computed tomography (DECT) and material decomposition play vital roles in quantitative medical imaging. However, the decomposition process may suffer from significant noise amplification, leading to severely degraded image signal-to-noise ratios (SNRs). While existing iterative algorithms perform noise suppression using different image priors, these heuristic image priors cannot accurately represent the features of the target image manifold. Although deep learning-based decomposition methods have been reported, these methods are in the supervised-learning framework requiring paired data for training, which is not readily available in clinical settings. PURPOSE: This work aims to develop an unsupervised-learning framework with data-measurement consistency for image-domain material decomposition in DECT. METHODS: The proposed framework combines iterative decomposition and deep learning-based image prior in a generative adversarial network (GAN) architecture. In the generator module, a data-fidelity loss is introduced to enforce the measurement consistency in material decomposition. In the discriminator module, the discriminator is trained to differentiate the low-noise material-specific images from the high-noise images. In this scheme, paired images of DECT and ground-truth material-specific images are not required for the model training. Once trained, the generator can perform image-domain material decomposition with noise suppression in a single step. RESULTS: In the simulation studies of head and lung digital phantoms, the proposed method reduced the standard deviation (SD) in decomposed images by 97% and 91% from the values in direct inversion results. It also generated decomposed images with structural similarity index measures (SSIMs) greater than 0.95 against the ground truth. In the clinical head and lung patient studies, the proposed method suppressed the SD by 95% and 93% compared to the decomposed images of matrix inversion. CONCLUSIONS: Since the invention of DECT, noise amplification during material decomposition has been one of the biggest challenges, impeding its quantitative use in clinical practice. The proposed method performs accurate material decomposition with efficient noise suppression. Furthermore, the proposed method is within an unsupervised-learning framework, which does not require paired data for model training and resolves the issue of lack of ground-truth data in clinical scenarios.

Niraparib enhances antitumor immunity and contributes to the efficacy of PD-L1 blockade in cervical cancer.

PURPOSE: With the development of immunotherapy research, the role of immune checkpoint blockade (ICB) in the treatment of cervical cancer has been emphasized, but many patients still can't receive long-term benefits from ICB. Poly ADP ribose polymerase inhibitor (PARPi) has been proved to exert significant antitumor effects in multiple solid tumors. Whether cervical cancer patients obtain better benefits from the treatment regimen of PARPi combined with ICB remains unclear. METHODS: The alteration of PD-L1 expression induced by niraparib in cervical cancer cells and its underlying mechanism were assessed by western blot and immunofluorescence and quantitative real-time polymerase chain reaction (qRT-PCR).The regulation of PTEN by KDM5A was confirmed using Chromatin immunoprecipitation (ChIP) assay and RNA interference. Analyzing the relationship between PD-L1 and immune effector molecules through searching online databases. Therapeutic efficacy of niraparib, PD-L1 blockade or combination was assessed in syngeneic tumor model. The changes of immune cells and cytokines in vivo was detected by immunohistochemistry (IHC) and qRT-PCR. RESULTS: We found that niraparib upregulated PD-L1 expression and potentiated the antitumor effects of PD-L1 blockade in a murine cervical cancer model. Niraparib inhibited the Pten expression by increasing the abundance of KDM5A, which expanded PD-L1 abundance through activating the PI3K-AKT-S6K1 pathway. PD-L1 was positively correlated with immune effector molecules including TNF-α, IFN-γ, granzyme A and granzyme B based on biological information analysis. Niraparib increased the infiltration of CD8+ T cells and the level of IFN-γ, granzyme B in vivo. CONCLUSION: Our findings demonstrates the regulation of niraparib on local immune microenvironment of cervical cancer, and provides theoretical basis for supporting the combination of PARPi and PD-L1 blockade as a potential treatment for cervical cancer.

Research and Analysis of Molecules such as CD28, CD45RA, CD45RO, CD38, HLA-DR, and CD57 on T Cells in Multiple Myeloma.

BACKGROUND: For many years it has been postulated that the immune system controls the progress of multiple myeloma (MM). However, the phenotypes of T cells in MM remain to be elucidated. In this study, we compared the phenotypes of T cells, which were obtained from the peripheral blood, in MM patients with those in healthy donors (HD). The expression of CCR7, CD57, CD28, HLA-DR, CD38, CD45RA, and CD45RO were assessed on T cells from MM patients and HDs using multicolor flow cytometry (MFC). METHODS: For this study, 17 newly diagnosed MM patients were selected, and 20 healthy people were selected as a control group. MFC was used to detect the markers on T cells. RESULTS: We detected significant increases in the expression levels of HLA-DR, CD38, and CD57on CD8+ T cells, significant decreases in the expression levels of CD28 and CD45RA on CD8+ T cells, and a decrease of CD4+ effec-tor T cells in MM patients, compared to the HD group. CONCLUSIONS: Our study shows that the accumulation of peripheral CD8+CD57+T cells, CD8+CD38high T cells, and CD8+HLA-DR+CD38high T cells is reflective of an ongoing antitumor T cell response and a progressive immune dysfunction in MM. During chemotherapy, the recovery of immune function can be monitored by detecting the proportion of activated molecules of T lymphocytes.

Adaptive Proton Therapy Using CBCT-Guided Digital Twins.

This study aims to develop a digital twin (DT) framework to enhance adaptive proton stereotactic body radiation therapy (SBRT) for prostate cancer. Prostate SBRT has emerged as a leading option for external beam radiotherapy due to its effectiveness and reduced treatment duration. However, interfractional anatomy variations can impact treatment outcomes. This study seeks to address these uncertainties using DT concept, with the goal of improving treatment quality, potentially revolutionizing prostate radiotherapy to offer personalized treatment solutions. Our study presented a pioneering approach that leverages DT technology to enhance adaptive proton SBRT. The framework improves treatment plans by utilizing patient-specific CTV setup uncertainty, which is usually smaller than conventional clinical setups. This research contributes to the ongoing efforts to enhance the efficiency and efficacy of prostate radiotherapy, with ultimate goals of improving patient outcomes and life quality.

Effect of High-Temperature Storage on Electrical Characteristics of Hydrogen-Treated AlGaN/GaN High-Electron-Mobility Transistors.

In this paper, high-temperature storage of hydrogen-treated AlGaN/GaN HEMTs is conducted for the first time to study the effect of high temperature on the electrical characteristics of the devices after hydrogen treatment, and it is found that high-temperature storage can effectively reduce the impact of hydrogen on the devices. After hydrogen treatment, the output current and the maximum transconductance of the device increase, and the threshold voltage drifts negatively. However, after high-temperature treatment at 200 °C for 24 h, the output current, threshold voltage, and the maximum transconductance of the device all approach their initial values before hydrogen treatment. By using low-frequency noise analysis technology, the trap density of the hydrogen-treated AlGaN/GaN HEMT is determined to be 8.9 × 1023 cm-3·eV-1, while it changes to 4.46 × 1022 cm-3·eV-1 after high-temperature storage. We believe that the change in the electrical characteristics of the device in hydrogen is due to the passivation of hydrogen on the inherent trap of the device, and the variation in the electrical properties of the device in the process of high-temperature storage involves the influence of two effects, namely the dehydrogenation effect and the improvement of the metal-semiconductor interface caused by high temperatures.

MRI-only based material mass density and relative stopping power estimation via deep learning for proton therapy: a preliminary study.

Magnetic Resonance Imaging (MRI) is increasingly being used in treatment planning due to its superior soft tissue contrast, which is useful for tumor and soft tissue delineation compared to computed tomography (CT). However, MRI cannot directly provide mass density or relative stopping power (RSP) maps, which are required for calculating proton radiotherapy doses. Therefore, the integration of artificial intelligence (AI) into MRI-based treatment planning to estimate mass density and RSP directly from MRI has generated significant interest. A deep learning (DL) based framework was developed to establish a voxel-wise correlation between MR images and mass density as well as RSP. To facilitate the study, five tissue substitute phantoms were created, representing different tissues such as skin, muscle, adipose tissue, 45% hydroxyapatite (HA), and spongiosa bone. The composition of these phantoms was based on information from ICRP reports. Additionally, two animal tissue phantoms, simulating pig brain and liver, were prepared for DL training purposes. The phantom study involved the development of two DL models. The first model utilized clinical T1 and T2 MRI scans as input, while the second model incorporated zero echo time (ZTE) MRI scans. In the patient application study, two more DL models were trained: one using T1 and T2 MRI scans as input, and another model incorporating synthetic dual-energy computed tomography (sDECT) images to provide accurate bone tissue information. The DECT empirical model was used as a reference to evaluate the proposed models in both phantom and patient application studies. The DECT empirical model was selected as the reference for evaluating the proposed models in both phantom and patient application studies. In the phantom study, the DL model based on T1, and T2 MRI scans demonstrated higher accuracy in estimating mass density and RSP for skin, muscle, adipose tissue, brain, and liver. The mean absolute percentage errors (MAPE) were 0.42%, 0.14%, 0.19%, 0.78%, and 0.26% for mass density, and 0.30%, 0.11%, 0.16%, 0.61%, and 0.23% for RSP, respectively. The DL model incorporating ZTE MRI further improved the accuracy of mass density and RSP estimation for 45% HA and spongiosa bone, with MAPE values of 0.23% and 0.09% for mass density, and 0.19% and 0.07% for RSP, respectively. These results demonstrate the feasibility of using an MRI-only approach combined with DL methods for mass density and RSP estimation in proton therapy treatment planning. By employing this approach, it is possible to obtain the necessary information for proton radiotherapy directly from MRI scans, eliminating the need for additional imaging modalities.

Enhancing the stability of a novel D-allulose 3-epimerase from Ruminococcus sp. CAG55 by interface interaction engineering and terminally attached a self-assembling peptide.

D-allulose, a highly desirable sugar substitute, is primarily produced using the D-allulose 3-epimerase (DAE). However, the availability of usable DAE enzymes is limited. In this study, we discovered and engineered a novel DAE Rum55, derived from a human gut bacterium Ruminococcus sp. CAG55. The activity of Rum55 was strictly dependent on the presence of Co2+, and it exhibited an equilibrium conversion rate of 30.6 % and a half-life of 4.5 h at 50 °C. To enhance its performance, we engineered the interface interaction of Rum55 to stabilize its tetramer structure, and the best variant E268R was then attached with a self-assembling peptide to form active enzyme aggregates as carrier-free immobilization. The half-life of the best variant E268R-EKL16 at 50 °C was dramatically increased 30-fold to 135.3 h, and it maintained 90 % of its activity after 13 consecutive reaction cycles. Additionally, we identified that metal ions played a key role in stabilizing the tetramer structure of Rum55, and the dependence on metal ions for E268R-EKL16 was significantly reduced. This study provides a useful route for improving the thermostability of DAEs, opening up new possibilities for the industrial production of D-allulose.

Identification and treatment of intestinal malrotation with midgut volvulus in childhood: a multicenter retrospective study.

Background: Intestinal malrotation is a rare condition, and its delayed diagnosis can lead to fatal consequences. This study aimed to investigate the identification and treatment of malrotation in children. Methods: Clinical data, imaging, operative findings, and early postoperative outcomes of 75 children with malrotation were retrospectively analyzed. Results: The mean age was 6.18 ± 4.93 days and 51.26 ± 70.13 months in the neonatal group (56 patients) and non-neonatal group (19 patients), respectively. Sixty-seven patients were under the age of 1 year at the time of diagnosis. The occurrence of bilious vomiting and jaundice was significantly higher in the neonatal group (89.29%) than that in the non-neonatal group (37.5%), p < 0.05 and p < 0.01, respectively. The incidence of abnormal ultrasound (US) findings was 97.30% and 100%, respectively, and the sensitivities of the upper gastrointestinal series were 84.21% and 87.5%, respectively. Sixty-six (88%) patients had midgut volvulus, including in utero volvulus (two patients) and irreversible intestinal ischemia (four patients). Most neonates (89.29%) underwent open Ladd's procedure with a shorter operative time (p < 0.01). Reoperation was performed for postoperative complications (four patients) or missed comorbidities (two patients). Conclusions: Non-bilious vomiting was the initial symptom in >10% of neonates and nearly 40% of non-neonates. This highlights the importance for emergency physicians and surgeons to be cautious about ruling out malrotation in patients with non-bilious vomiting. Utilizing US can obviate the need for contrast examinations owing to its higher diagnostic accuracy and rapid diagnosis and can be recommended as a first-line imaging technique. Additionally, open surgery is still an option for neonatal patients.

Clinical features and treatment of heterotopic pancreas in children: a multi-center retrospective study.

OBJECTIVE: Heterotopic pancreas, an uncommon condition in children, can present with diagnostic and treatment challenges. This study aimed to evaluate the clinical features and treatment options for this disorder in pediatric patients. METHODS: We conducted a retrospective analysis, including patients diagnosed with heterotopic pancreas at four tertiary hospitals between January 2000 and June 2022. Patients were categorized into symptomatic and asymptomatic groups based on clinical presentation. Clinical parameters, including age at surgery, lesion size and site, surgical or endoscopic approach, pathological findings, and outcome, were statistically analyzed. RESULTS: The study included 88 patients with heterotopic pancreas. Among them, 22 were symptomatic, and 41 were aged one year or younger. The heterotopic pancreas was commonly located in Meckel's diverticulum (46.59%), jejunum (20.45%), umbilicus (10.23%),ileum (7.95%), and stomach (6.82%). Sixty-six patients had concomitant diseases. Thirty-three patients had heterotopic pancreas located in the Meckel's diverticulum, with 80.49% of cases accompanied by gastric mucosa heterotopia (GMH). Patients without accompanying GMH had a higher prevalence of heterotopic pancreas-related symptoms (75%). Treatment modalities included removal of the lesions by open surgery, laparoscopic or laparoscopic assisted surgery, or endoscopic surgery based on patient's age, the lesion site and size, and coexisting diseases. CONCLUSIONS: Only one-fourth of the patients with heterotopic pancreas presented with symptoms. Those located in the Meckel's diverticulum have commonly accompanying GMH. Open surgical, laparoscopic surgical or endoscopic resection of the heterotopic pancreas is recommended due to potential complications. Future prospective multicenter studies are warranted to establish rational treatment options.

Cardiac MRI segmentation using shifted-window multilayer perceptron mixer networks.

Objectives. In this work, we proposed a deep-learning segmentation algorithm for cardiac magnetic resonance imaging to aid in contouring of the left ventricle, right ventricle, and Myocardium (Myo).Approach.We proposed a shifted window multilayer perceptron (Swin-MLP) mixer network which is built upon a 3D U-shaped symmetric encoder-decoder structure. We evaluated our proposed network using public data from 100 individuals. The network performance was quantitatively evaluated using 3D volume similarity between the ground truth contours and the predictions using Dice score coefficient, sensitivity, and precision as well as 2D surface similarity using Hausdorff distance (HD), mean surface distance (MSD) and residual mean square distance (RMSD). We benchmarked the performance against two other current leading edge networks known as Dynamic UNet and Swin-UNetr on the same public dataset.Results.The proposed network achieved the following volume similarity metrics when averaged over three cardiac segments: Dice = 0.952 ± 0.017, precision = 0.948 ± 0.016, sensitivity = 0.956 ± 0.022. The average surface similarities were HD = 1.521 ± 0.121 mm, MSD = 0.266 ± 0.075 mm, and RMSD = 0.668 ± 0.288 mm. The network shows statistically significant improvement in comparison to the Dynamic UNet and Swin-UNetr algorithms for most volumetric and surface metrics withp-value less than 0.05. Overall, the proposed Swin-MLP mixer network demonstrates better or comparable performance than competing methods.Significance.The proposed Swin-MLP mixer network demonstrates more accurate segmentation performance compared to current leading edge methods. This robust method demonstrates the potential to streamline clinical workflows for multiple applications.

A metal-phenolic coordination framework nanozyme exhibits dual enzyme mimicking activity and its application is effective for colorimetric detection of biomolecules.

Biomolecules play vital roles in many biological processes and diseases, making their identification crucial. Herein, we present a colorimetric sensing method for detecting biomolecules like cysteine (Cys), homocysteine (Hcy), and glutathione (GSH). This approach is based on a reaction system whereby colorless 3,3',5,5'-tetramethylbenzidine (TMB) undergoes catalytic oxidation to form blue-colored oxidized TMB (ox-TMB) in the presence of hydrogen peroxide (H2O2), utilizing the peroxidase and catalase-mimicking activities of metal-phenolic coordination frameworks (MPNs) of Cu-TA, Co-TA, and Fe-TA nanospheres. The Fe-TA nanospheres demonstrated superior activity, more active sites and enhanced electron transport. Under optimal conditions, the Fe-TA nanospheres were used for the detection of biomolecules. When present, biomolecules inhibit the reaction between TMB and H2O2, causing various colorimetric responses at low detection limits of 0.382, 0.776 and 0.750 µM for Cys, Hcy and GSH. Furthermore, it was successfully applied to real water samples with good recovery results. The developed sensor not only offers a rapid, portable, and user-friendly technique for multi-target analysis of biomolecules at low concentrations but also expands the potential uses of MPNs for other targets in the environmental field.

Polyurethane-based three-dimensional printing for biological mesh carriers.

Repair and reconstruction of the myopectineal orifice area using meshes is the mainstay of surgical treatment of inguinal hernias. However, the limitations of existing meshes are becoming increasingly evident in clinical applications; thus, the idea of using three-dimensionally (3D)-printed biological meshes was put forward. According to the current level of the 3D printing technology and the inherent characteristics of biological materials, the direct use of the 3D printing technology for making biological materials into finished products suitable for clinical applications is not yet supported, but synthetic materials can be first printed into 3D form carriers, compounded with biological materials, and finally made into finished products. The purpose of this study was to develop a technical protocol for making 3D-printed biomesh carriers using polyurethane as a raw material. In our study: raw material, polyurethane; weight, 20-30 g/m2; weaving method, hexagonal mesh; elastic tension aspect ratio, 2:1; diameters of pores, 0.1-1 mm; surface area, 8 × 12 cm2; the optimal printing layer height, temperature and velocity were 0.1 mm, 210-220 °C and 60 mm/s. Its clinical significance lies in: (1) applied to preoperative planning and design a detailed surgical plan; (2) applied to special types of surgery including patients in puberty, recurrent and compound inguinal hernias; (3) significantly improve the efficiency of doctor-patient communication; (4) it can shorten the operation and recovery period by about 1/3 and can save about 1/4 of the cost for patients; (5) the learning curve is significantly shortened, which is conducive to the cultivation of reserve talents.

Unsupervised MRI motion artifact disentanglement: introducing MAUDGAN.

Objective.This study developed an unsupervised motion artifact reduction method for magnetic resonance imaging (MRI) images of patients with brain tumors. The proposed novel design uses multi-parametric multicenter contrast-enhanced T1W (ceT1W) and T2-FLAIR MRI images.Approach.The proposed framework included two generators, two discriminators, and two feature extractor networks. A 3-fold cross-validation was used to train and fine-tune the hyperparameters of the proposed model using 230 brain MRI images with tumors, which were then tested on 148 patients'in-vivodatasets. An ablation was performed to evaluate the model's compartments. Our model was compared with Pix2pix and CycleGAN. Six evaluation metrics were reported, including normalized mean squared error (NMSE), structural similarity index (SSIM), multi-scale-SSIM (MS-SSIM), peak signal-to-noise ratio (PSNR), visual information fidelity (VIF), and multi-scale gradient magnitude similarity deviation (MS-GMSD). Artifact reduction and consistency of tumor regions, image contrast, and sharpness were evaluated by three evaluators using Likert scales and compared with ANOVA and Tukey's HSD tests.Main results.On average, our method outperforms comparative models to remove heavy motion artifacts with the lowest NMSE (18.34±5.07%) and MS-GMSD (0.07 ± 0.03) for heavy motion artifact level. Additionally, our method creates motion-free images with the highest SSIM (0.93 ± 0.04), PSNR (30.63 ± 4.96), and VIF (0.45 ± 0.05) values, along with comparable MS-SSIM (0.96 ± 0.31). Similarly, our method outperformed comparative models in removingin-vivomotion artifacts for different distortion levels except for MS- SSIM and VIF, which have comparable performance with CycleGAN. Moreover, our method had a consistent performance for different artifact levels. For the heavy level of motion artifacts, our method got the highest Likert scores of 2.82 ± 0.52, 1.88 ± 0.71, and 1.02 ± 0.14 (p-values≪0.0001) for our method, CycleGAN, and Pix2pix respectively. Similar trends were also found for other motion artifact levels.Significance.Our proposed unsupervised method was demonstrated to reduce motion artifacts from the ceT1W brain images under a multi-parametric framework.