Unsupervised MRI motion artifact disentanglement: introducing MAUDGAN.

OBJECTIVE: This study developed an unsupervised motion artifact reduction method for 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-vivo datasets. 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 removing in-vivo motion 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.

Overexpressed Trophoblast Glycoprotein Contributes to Preeclampsia Development by Inducing Abnormal Trophoblast Migration and Invasion Toward the Uterine Spiral Artery.

BACKGROUND: Preeclampsia is a significant pregnancy disorder with an unknown cause, mainly attributed to impaired spiral arterial remodeling. METHODS: Using RNA sequencing, we identified key genes in placental tissues from healthy individuals and preeclampsia patients. Placenta and plasma samples from pregnant women were collected to detect the expression of TPBG (trophoblast glycoprotein). Pregnant rats were injected with TPBG-carrying adenovirus to detect preeclamptic features. HTR-8/SVneo cells transfected with a TPBG overexpression lentiviral vector were used in cell function experiments. The downstream molecular mechanisms of TPBG were explored using RNA sequencing and single-cell RNA sequencing data. TPBG expression was knocked down in the lipopolysaccharide-induced preeclampsia-like rat model to rescue the preeclampsia features. We also assessed TPBG's potential as an early preeclampsia predictor using clinical plasma samples. RESULTS: TPBG emerged as a crucial differentially expressed gene, expressed specifically in syncytiotrophoblasts and extravillous trophoblasts. Subsequently, we established a rat model with preeclampsia-like phenotypes by intravenously injecting TPBG-expressing adenoviruses, observing impaired spiral arterial remodeling, thus indicating a causal correlation between TPBG overexpression and preeclampsia. Studies with HTR-8/SVneo cells, chorionic villous explants, and transwell assays showed TPBG overexpression disrupts trophoblast/extravillous trophoblast migration/invasion and chemotaxis. Notably, TPBG knockdown alleviated the lipopolysaccharide-induced preeclampsia-like rat model. We enhanced preeclampsia risk prediction in early gestation by combining TPBG expression with established clinical predictors. CONCLUSIONS: These findings are the first to show that TPBG overexpression contributes to preeclampsia development by affecting uterine spiral artery remodeling. We propose TPBG levels in maternal blood as a predictor of preeclampsia risk. The proposed mechanism by which TPBG overexpression contributes to the occurrence of preeclampsia via its disruptive effect on trophoblast and extravillous trophoblast migration/invasion on uterine spiral artery remodeling, thereby increasing the risk of preeclampsia.

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.

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.

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.

Single-Cell Analyses Offer Insights into the Different Remodeling Programs of Arteries and Veins.

Arteries and veins develop different types of occlusive diseases and respond differently to injury. The biological reasons for this discrepancy are not well understood, which is a limiting factor for the development of vein-targeted therapies. This study contrasts human peripheral arteries and veins at the single-cell level, with a focus on cell populations with remodeling potential. Upper arm arteries (brachial) and veins (basilic/cephalic) from 30 organ donors were compared using a combination of bulk and single-cell RNA sequencing, proteomics, flow cytometry, and histology. The cellular atlases of six arteries and veins demonstrated a 7.8× higher proportion of contractile smooth muscle cells (SMCs) in arteries and a trend toward more modulated SMCs. In contrast, veins showed a higher abundance of endothelial cells, pericytes, and macrophages, as well as an increasing trend in fibroblasts. Activated fibroblasts had similar proportions in both types of vessels but with significant differences in gene expression. Modulated SMCs and activated fibroblasts were characterized by the upregulation of MYH10, FN1, COL8A1, and ITGA10. Activated fibroblasts also expressed F2R, POSTN, and COMP and were confirmed by F2R/CD90 flow cytometry. Activated fibroblasts from veins were the top producers of collagens among all fibroblast populations from both types of vessels. Venous fibroblasts were also highly angiogenic, proinflammatory, and hyper-responders to reactive oxygen species. Differences in wall structure further explain the significant contribution of fibroblast populations to remodeling in veins. Fibroblasts are almost exclusively located outside the external elastic lamina in arteries, while widely distributed throughout the venous wall. In line with the above, ECM-targeted proteomics confirmed a higher abundance of fibrillar collagens in veins vs. more basement ECM components in arteries. The distinct cellular compositions and transcriptional programs of reparative populations in arteries and veins may explain differences in acute and chronic wall remodeling between vessels. This information may be relevant for the development of antistenotic therapies.

A comparative study of two thienopyrimidine Schiff base probes for sequential monitoring of Ga3+ and Pd2.

Two Schiff base probes (S1 and S2) were prepared and synthesized by incorporating thienopyrimidine into salicylaldehyde or 3-ethoxysalicylaldehyde individually, with the aim of detecting Ga3+ and Pd2+ sequentially. Upon chelation with Ga3+, S1 and S2 exhibited fluorescence enhancement in DMSO/H2O buffer. Both S1-Ga3+ and S2-Ga3+ were quenched by Pd2+. The limit of detection for S1 in response to Ga3+ and Pd2+ was 2.86 × 10-7 and 4.4 × 10-9 M, respectively. For S2, the limit of detection for Ga3+ and Pd2+ was 4.15 × 10-8 and 3.0 × 10-9 M, respectively. Furthermore, the complexation ratios of both S1 and S2 with Ga3+ and Pd2+ were determined to be 1:2 through Job's plots, ESI-MS analysis, and theoretical calculations. Two molecular logic gates were constructed, leveraging the response behaviors of S1 and S2. Moreover, the potential utility of S1 and S2 for monitoring Ga3+ and Pd2+ in domestic water was verified.

Applying improved ddPCR to reliable quantification of MPXV in clinical settings.

Monkeypox virus (MPXV) poses a global health threat. Droplet digital PCR (ddPCR) holds potential as an accurate diagnostic tool for clinical microbiology. However, there is limited literature on the applicability of ddPCR in clinical settings. In this study, the clinical features of patients with MPXV during the initial outbreak in China in June 2023 were reviewed, and an optimized ddPCR method with dilution and/or inhibitor removal was developed to enhance MPXV detection efficiency. Eighty-two MPXV samples were tested from nine different clinical specimen types, including feces, urine, pharyngeal swabs, anal swabs, saliva, herpes fluid, crust, and semen, and the viral load of each specimen was quantified. A comparative analysis was performed with qPCR to assess sensitivity and specificity and to investigate the characteristics of MPXV infection by analyzing viral loads in different clinical specimens. Consequently, common pharyngeal and gastrointestinal symptoms were observed in patients with MPXV. The optimized ddPCR method demonstrated relatively high sensitivity for MPXV quantification in the clinical materials, with a limit of detection of 0.1 copies/µL. This was particularly evident in low-concentration samples like whole blood, semen, and urine. The optimized ddPCR demonstrated greater detection accuracy compared with normal ddPCR and qPCR, with an area under the curve (AUC) of 0.939. Except for crust samples, viral loads in the specimens gradually decreased as the disease progressed. Virus levels in feces and anal swabs kept a high detection rate at each stage of post-symptom onset, and feces and anal swabs samples may be suitable for clinical diagnosis and continuous monitoring of MPXV. IMPORTANCE: The ddPCR technique proved to be a sensitive and valuable tool for accurately quantifying MPXV viral loads in various clinical specimen types. The findings provided valuable insights into the necessary pre-treatment protocols for MPXV diagnosis in ddPCR detection and the potentially suitable sample types for collection. Therefore, such results can aid in comprehending the potential characteristics of MPXV infection and the usage of ddPCR in clinical settings.

Customizable Click Biochemistry Strategy for the Design and Preparation of Glucagon-like Peptide-1 Conjugates and Coagonists.

The development of oligomeric glucagon-like peptide-1 (GLP-1) and GLP-1-containing coagonists holds promise for enhancing the therapeutic potential of the GLP-1-based drugs for treating type 2 diabetes mellitus (T2DM). Here, we report a facile, efficient, and customizable strategy based on genetically encoded SpyCatcher-SpyTag chemistry and an inducible, cleavable self-aggregating tag (icSAT) scheme. icSAT-tagged SpyTag-fused GLP-1 and the dimeric or trimeric SpyCatcher scaffold were designed for dimeric or trimeric GLP-1, while icSAT-tagged SpyCatcher-fused GLP-1 and the icSAT-tagged SpyTag-fused GIP were designed for dual GLP-1/GIP (glucose-dependent insulinotropic polypeptide) receptor agonist. These SpyCatcher- and SpyTag-fused protein pairs were spontaneously ligated directly from the cell lysates. The subsequent icSAT scheme, coupled with a two-step standard column purification, resulted in target proteins with authentic N-termini, with yields ranging from 35 to 65 mg/L and purities exceeding 99%. In vitro assays revealed 3.0- to 4.1-fold increased activities for dimeric and trimeric GLP-1 compared to mono-GLP-1. The dual GLP-1/GIP receptor agonist exhibited balanced activity toward the GLP-1 receptor or the GIP receptor. All the proteins exhibited 1.8- to 3.0-fold prolonged half-lives in human serum compared to mono-GLP-1 or GIP. This study provides a generally applicable click biochemistry strategy for developing oligomeric or dual peptide/protein-based drug candidates.

SAH is a major metabolic sensor mediating worsening metabolic crosstalk in metabolic syndrome.

In this study, we observed worsening metabolic crosstalk in mouse models with concomitant metabolic disorders such as hyperhomocysteinemia (HHcy), hyperlipidemia, and hyperglycemia and in human coronary artery disease by analyzing metabolic profiles. We found that HHcy worsening is most sensitive to other metabolic disorders. To identify metabolic genes and metabolites responsible for the worsening metabolic crosstalk, we examined mRNA levels of 324 metabolic genes in Hcy, glucose-related and lipid metabolic systems. We examined Hcy-metabolites (Hcy, SAH and SAM) by LS-ESI-MS/MS in 6 organs (heart, liver, brain, lung, spleen, and kidney) from C57BL/6J mice. Through linear regression analysis of Hcy-metabolites and metabolic gene mRNA levels, we discovered that SAH-responsive genes were responsible for most metabolic changes and all metabolic crosstalk mediated by Serine, Taurine, and G3P. SAH-responsive genes worsen glucose metabolism and cause upper glycolysis activation and lower glycolysis suppression, indicative of the accumulation of glucose/glycogen and G3P, Serine synthesis inhibition, and ATP depletion. Insufficient Serine due to negative correlation of PHGDH with SAH concentration may inhibit the folate cycle and transsulfurarion pathway and consequential reduced antioxidant power, including glutathione, taurine, NADPH, and NAD+. Additionally, we identified SAH-activated pathological TG loop as the consequence of increased fatty acid (FA) uptake, FA ß-oxidation and Ac-CoA production along with lysosomal damage. We concluded that HHcy is most responsive to other metabolic changes in concomitant metabolic disorders and mediates worsening metabolic crosstalk mainly via SAH-responsive genes, that organ-specific Hcy metabolism determines organ-specific worsening metabolic reprogramming, and that SAH, acetyl-CoA, Serine and Taurine are critical metabolites mediating worsening metabolic crosstalk, redox disturbance, hypomethylation and hyperacetylation linking worsening metabolic reprogramming in metabolic syndrome.

Diffeomorphic Transformer-based Abdomen MRI-CT Deformable Image Registration.

Background: Stereotactic body radiotherapy (SBRT) is a well-established treatment modality for liver metastases in patients unsuitable for surgery. Both CT and MRI are useful during treatment planning for accurate target delineation and to reduce potential organs-at-risk (OAR) toxicity from radiation. MRI-CT deformable image registration (DIR) is required to propagate the contours defined on high-contrast MRI to CT images. An accurate DIR method could lead to more precisely defined treatment volumes and superior OAR sparing on the treatment plan. Therefore, it is beneficial to develop an accurate MRI-CT DIR for liver SBRT. Purpose: To create a new deep learning model that can estimate the deformation vector field (DVF) for directly registering abdominal MRI-CT images. Methods: The proposed method assumed a diffeomorphic deformation. By using topology-preserved deformation features extracted from the probabilistic diffeomorphic registration model, abdominal motion can be accurately obtained and utilized for DVF estimation. The model integrated Swin transformers, which have demonstrated superior performance in motion tracking, into the convolutional neural network (CNN) for deformation feature extraction. The model was optimized using a cross-modality image similarity loss and a surface matching loss. To compute the image loss, a modality-independent neighborhood descriptor (MIND) was used between the deformed MRI and CT images. The surface matching loss was determined by measuring the distance between the warped coordinates of the surfaces of contoured structures on the MRI and CT images. To evaluate the performance of the model, a retrospective study was carried out on a group of 50 liver cases that underwent rigid registration of MRI and CT scans. The deformed MRI image was assessed against the CT image using the target registration error (TRE), Dice similarity coefficient (DSC), and mean surface distance (MSD) between the deformed contours of the MRI image and manual contours of the CT image. Results: When compared to only rigid registration, DIR with the proposed method resulted in an increase of the mean DSC values of the liver and portal vein from 0.850±0.102 and 0.628±0.129 to 0.903±0.044 and 0.763±0.073, a decrease of the mean MSD of the liver from 7.216±4.513 mm to 3.232±1.483 mm, and a decrease of the TRE from 26.238±2.769 mm to 8.492±1.058 mm. Conclusion: The proposed DIR method based on a diffeomorphic transformer provides an effective and efficient way to generate an accurate DVF from an MRI-CT image pair of the abdomen. It could be utilized in the current treatment planning workflow for liver SBRT.

Fast MRI Reconstruction Using Deep Learning-based Compressed Sensing: A Systematic Review.

Magnetic resonance imaging (MRI) has revolutionized medical imaging, providing a non-invasive and highly detailed look into the human body. However, the long acquisition times of MRI present challenges, causing patient discomfort, motion artifacts, and limiting real-time applications. To address these challenges, researchers are exploring various techniques to reduce acquisition time and improve the overall efficiency of MRI. One such technique is compressed sensing (CS), which reduces data acquisition by leveraging image sparsity in transformed spaces. In recent years, deep learning (DL) has been integrated with CS-MRI, leading to a new framework that has seen remarkable growth. DL-based CS-MRI approaches are proving to be highly effective in accelerating MR imaging without compromising image quality. This review comprehensively examines DL-based CS-MRI techniques, focusing on their role in increasing MR imaging speed. We provide a detailed analysis of each category of DL-based CS-MRI including end-to-end, unroll optimization, self-supervised, and federated learning. Our systematic review highlights significant contributions and underscores the exciting potential of DL in CS-MRI. Additionally, our systematic review efficiently summarizes key results and trends in DL-based CS-MRI including quantitative metrics, the dataset used, acceleration factors, and the progress of and research interest in DL techniques over time. Finally, we discuss potential future directions and the importance of DL-based CS-MRI in the advancement of medical imaging. To facilitate further research in this area, we provide a GitHub repository that includes up-to-date DL-based CS-MRI publications and publicly available datasets - https://github.com/mosaf/Awesome-DL-based-CS-MRI.

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.

Relationship Between the Gut Microbiota and Neurological Deficits in Patients With Cerebral Ischemic Stroke.

OBJECTIVE: The aim of the paper was to investigate the composition and structure of intestinal flora in patients with cerebral ischemic stroke (CIS), and to investigate the relationship between gut microbiota (GM) and different levels of stroke severity. METHODS: In this study, 47 CIS patients (16 mild, 21 moderate, and 10 severe) and 15 healthy controls were included. General information, clinical data, and behavioral scores of the enrolled subjects were collected. Deoxyribonucleic acid in fecal intestinal flora was extracted and detected using high-throughput Illumina 16S ribosomal ribonucleic acid sequencing technology. Finally, the correlation between the community composition of intestinal microbiota and National Institutes of Health Stroke Scale (NIHSS) score in CIS patients was analyzed. RESULTS: Compared with healthy controls, there was no statistically significant difference in Alpha diversity among CIS patients, but the principal coordinate analysis showed significant differences in the composition of the GM among stroke patients with different degrees of severity and controls. In CIS patients, Streptococcus was significantly enriched, and Eshibacter-Shigella, Bacteroides, and Agathobacter were significantly down-regulated (P < .05). In addition, the relative abundance of Blautia was negatively correlated with the NIHSS score. CONCLUSIONS: Our results show that different degrees of CIS severity exert distinct effects on the intestinal microbiome. This study reveals the intestinal microecological changes after brain injury from the perspective of brain-gut axis. Intestinal microorganisms not only reveal the possible pathological process and indicate the severity of neurologic impairment, but also make targeted therapy possible for CIS patients.

Up-regulated ORC1 promotes lung adenocarcinoma by inhibiting ferroptosis via SLC7A11 dependent pathway.

Background: Lung adenocarcinoma (LUAD) is a pulmonary malignant disease that poses a high risk of mortality and morbidity. Previous study indicated that ORC1 plays an oncogenic function. However, the precise regulatory function that ORC1 serves in the progression of LUAD is still not clearly known. Methods: Bioinformatics analyses were performed using TCGA and GEO datasets. The human LUAD cell line NCIH1355, NCIH1568 as well as BEAS-2B cell line (human normal lung epithelial cell) were utilized for in vitro study. LUAD cell proliferation were determined via CCK-8 assays and RT-qPCR for ki-67. The relation of ORC1 and SLC7A11 was detected by Western blot and qPCR with or without sh-RNA. The expression level ACSL4, the biomarker of ferroptosis, were detected using RT-qPCR. Results: ORC1 and SLC7A11 exhibit high expression levels in both LUAD patients and cell lines, and are strongly associated with poor prognosis. In vitro experiments demonstrate that ORC1 and SLC7A11 promote proliferation of LUAD cell lines while inhibiting gefitinib-induced ferroptosis. Additionally, the function of ORC1 in LUAD cells is dependent on SLC7A11. Conclusion: ORC1 promotes LUAD cell proliferation and inhibits ferroptosis in a SLC7A11-dependent manner. This implies that ORC1 could potentially serve as a useful diagnosis biomarker and treatment target.

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.