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.

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.

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.

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.

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.

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.

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.

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.

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.

Legumain-Triggered Macrocyclization of Radiofluorinated Tracer for Enhanced PET Imaging.

Enhancing the accumulation and retention of small-molecule probes in tumors is an important way to achieve accurate cancer diagnosis and therapy. Enzyme-stimulated macrocyclization of small molecules possesses great potential for enhanced positron emission tomography (PET) imaging of tumors. Herein, we reported an 18F-labeled radiotracer [18F]AlF-RSM for legumain detection in vivo. The tracer was prepared by a one-step aluminum-fluoride-restrained complexing agent ([18F]AlF-RESCA) method with high radiochemical yield (RCY) (88.35 ± 3.93%) and radiochemical purity (RCP) (>95%). More notably, the tracer can be transformed into a hydrophobic macrocyclic molecule under the joint action of legumain and reductant. Simultaneously, the tracer could target legumain-positive tumors and enhance accumulation and retention in tumors, resulting in the amplification of PET imaging signals. The enhancement of radioactivity enables PET imaging of legumain activity with high specificity. We envision that, by combining this highly efficient 18F-labeled strategy with our intramolecular macrocyclization reaction, a range of radiofluorinated tracers can be designed for tumor PET imaging and early cancer diagnosis in the future.

Intracorporeal versus extracorporeal anastomosis in laparoscopic right hemicolectomy for overweight colon cancer patients: a case-control study.

INTRODUCTION: Either extracorporeal anastomosis (EA) or intracorporeal anastomosis (IA) could be selected for digestive reconstruction in laparoscopic right hemicolectomy (LRH). However, whether LRH with IA is feasible and beneficial for overweight right-side colon cancer (RCC) is unclear. This study aims to investigate the feasibility and advantage of IA in LRH for overweight RCC. METHODS: Forty-eight consecutive overweight RCC patients undergoing LRH with IA were matched with 48 consecutive cases undergoing LRH with EA. Both clinical and surgical data were collected and analyzed. RESULTS: The incidence of postoperative complications was 20.8% (10/48) in the EA group and 14.6% (7/48) in the IA group respectively, with no statistical difference. Compared to the EA group, patients in the IA group revealed faster gas (40.2 + 7.8 h vs. 45.6 + 7.9 h, P = 0.001) and stool discharge (4.0 + 1.2 d vs. 4.5 + 1.1 d, P = 0.040), shorter assisted incision (5.3 + 1.3 cm vs. 7.5 + 1.2 cm, P = 0.000), and less analgesic used (3.3 + 1.3 d vs. 4.0 + 1.3 d, P = 0.012). There were no significant differences in operation time, blood loss, or postoperative hospital stays. In the IA group, the first one third of cases presented longer operation time (228.4 + 29.3 min) compared to the middle (191.0 + 35.0 min, P = 0.003) and the last one third of patients (182.2 + 20.7 min, P = 0.000). CONCLUSION: LRH with IA is feasible and safe for overweight RCC, with faster bowel function recovery and less pain. Accumulation of certain cases of LRH with IA will facilitate surgical procedures and reduce operation time.

Near-infrared fluorescence-assisted superficial inguinal lymph-node excision for low-risk penile cancer.

OBJECTIVE: Identification of superficial inguinal lymph nodes during low-risk penile cancer surgery using near-infrared (NIR) fluorescence to improve the accuracy of lymph-node dissection and reduce the incidence of missed micrometastases and complications. METHODS: Thirty-two cases were selected, which were under the criteria of < T1, and no lymph-node metastasis was found with magnetic resonance imaging (MRI) detection. Two groups were randomly divided based on the fluorescence technique, the indocyanine green (ICG) group and the non-ICG group. In the ICG group, the ICG preparation was subcutaneously injected into the edge of the penile tumor 10 min before surgery, and the near-infrared fluorescence imager was used for observation. After the lymph nodes were visualized, the superficial inguinal lymph nodes were removed first, and then, the penis surgery was performed. The non-ICG group underwent superficial inguinal lymph-node dissection and penile surgery. RESULTS: Among the 16 patients in the ICG group, we obtained 11 lymph-node specimens using grayscale values of images (4.13 ± 0.72 vs. 3.00 ± 0.82 P = 0.003) along with shorter postoperative healing time (7.31 ± 1.08 vs. 8.88 ± 2.43 P = 0.025), and less lymphatic leakage (0 vs. 5 P = 0.04) than the 16 patients in the non-ICG group. Out of 11, 3 lymph nodes that are excised were further grouped into fluorescent and non-fluorescent regions (G1/G2) and found to be metastasized. CONCLUSION: Near-infrared fluorescence-assisted superficial inguinal lymph-node dissection in penile carcinoma is accurate and effective, and could reduce surgical complications.

High-resolution 3T to 7T ADC map synthesis with a hybrid CNN-transformer model.

BACKGROUND: 7 Tesla (7T) apparent diffusion coefficient (ADC) maps derived from diffusion-weighted imaging (DWI) demonstrate improved image quality and spatial resolution over 3 Tesla (3T) ADC maps. However, 7T magnetic resonance imaging (MRI) currently suffers from limited clinical unavailability, higher cost, and increased susceptibility to artifacts. PURPOSE: To address these issues, we propose a hybrid CNN-transformer model to synthesize high-resolution 7T ADC maps from multimodal 3T MRI. METHODS: The Vision CNN-Transformer (VCT), composed of both Vision Transformer (ViT) blocks and convolutional layers, is proposed to produce high-resolution synthetic 7T ADC maps from 3T ADC maps and 3T T1-weighted (T1w) MRI. ViT blocks enabled global image context while convolutional layers efficiently captured fine detail. The VCT model was validated on the publicly available Human Connectome Project Young Adult dataset, comprising 3T T1w, 3T DWI, and 7T DWI brain scans. The Diffusion Imaging in Python library was used to compute ADC maps from the DWI scans. A total of 171 patient cases were randomly divided into 130 training cases, 20 validation cases, and 21 test cases. The synthetic ADC maps were evaluated by comparing their similarity to the ground truth volumes with the following metrics: peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and mean squared error (MSE). In addition, RESULTS: The results are as follows: PSNR: 27.0 ± 0.9 dB, SSIM: 0.945 ± 0.010, and MSE: 2.0E-3 ± 0.4E-3. Both qualitative and quantitative results demonstrate that VCT performs favorably against other state-of-the-art methods. We have introduced various efficiency improvements, including the implementation of flash attention and training on 176×208 resolution images. These enhancements have resulted in the reduction of parameters and training time per epoch by 50% in comparison to ResViT. Specifically, the training time per epoch has been shortened from 7.67 min to 3.86 min. CONCLUSION: We propose a novel method to predict high-resolution 7T ADC maps from low-resolution 3T ADC maps and T1w MRI. Our predicted images demonstrate better spatial resolution and contrast compared to 3T MRI and prediction results made by ResViT and pix2pix. These high-quality synthetic 7T MR images could be beneficial for disease diagnosis and intervention, producing higher resolution and conformal contours, and as an intermediate step in generating synthetic CT for radiation therapy, especially when 7T MRI scanners are unavailable.

A near-infrared fluorescence probe with large Stokes shift for selectively monitoring nitroreductase in living cells and mouse tumor models.

Hypoxia is commonly regarded as a typical feature of solid tumors, which originates from the insufficient supply of oxygen. Herein, the development of an efficient method for assessing hypoxia levels in tumors is strongly desirable. Nitroreductase (NTR) is an overexpressed reductase in the solid tumors, has been served as a potential biomarker to evaluate the degrees of hypoxia. In this work, we elaborately synthesized a new near-infrared (NIR) fluorescence probe (MR) to monitor NTR activity for assessment of hypoxia levels in living cells and in tumors. Upon exposure of NTR, the nitro-unit of MR could be selectively reduced to amino-moiety with the help of nicotinamide adenine dinucleotide. Moreover, the obtained fluorophore emitted a prominent NIR fluorescence, because it possessed a classical "push-pull" structure. The MR displayed several distinguished characters toward NTR, including intense NIR fluorescent signals, large Stokes shift, high selectivity and low limit of detection (46 ng/mL). Furthermore, cellular confocal fluorescence imaging results validated that the MR had potential of detecting NTR levels in hypoxic cells. Significantly, using the MR, the elevated of NTR levels were successfully visualized in the tumor-bearing mouse models. Therefore, this detecting platform based on this probe may be tactfully constructed for monitoring the variations of NTR and estimating the degrees of hypoxia in tumors.

Hemodynamic property incorporated brain tumor segmentation by deep learning and density-based analysis of dynamic susceptibility contrast-enhanced magnetic resonance imaging (MRI).

Background: Magnetic resonance imaging (MRI) is a primary non-invasive imaging modality for tumor segmentation, leveraging its exceptional soft tissue contrast and high resolution. Current segmentation methods typically focus on structural MRI, such as T1-weighted post-contrast-enhanced or fluid-attenuated inversion recovery (FLAIR) sequences. However, these methods overlook the blood perfusion and hemodynamic properties of tumors, readily derived from dynamic susceptibility contrast (DSC) enhanced MRI. This study introduces a novel hybrid method combining density-based analysis of hemodynamic properties in time-dependent perfusion imaging with deep learning spatial segmentation techniques to enhance tumor segmentation. Methods: First, a U-Net convolutional neural network (CNN) is employed on structural images to delineate a region of interest (ROI). Subsequently, Hierarchical Density-Based Scans (HDBScan) are employed within the ROI to augment segmentation by exploring intratumoral hemodynamic heterogeneity through the investigation of tumor time course profiles unveiled in DSC MRI. Results: The approach was tested and evaluated using a cohort of 513 patients from the open-source University of Pennsylvania glioblastoma database (UPENN-GBM) dataset, achieving a 74.83% Intersection over Union (IoU) score when compared to structural-only segmentation. The algorithm also exhibited increased precision and localized predictions of heightened segmentation boundary complexity, resulting in a 146.92% increase in contour complexity (ICC) compared to the reference standard provided by the UPENN-GBM dataset. Importantly, segmenting tumors with the developed new approach uncovered a negative correlation of the tumor volume with the scores in the Karnofsky Performance Scale (KPS) clinically used for assessing the functional status of patients (-0.309), which is not observed with the prevailing segmentation standard. Conclusions: This work demonstrated that including hemodynamic properties of tissues from DSC MRI can improve existing structural or morphological feature-based tumor segmentation techniques with additional information on tumor biology and physiology. This approach can also be applied to other clinical indications that use perfusion MRI for diagnosis or treatment monitoring.

Take CT, get PET free: AI-powered breakthrough in lung cancer diagnosis and prognosis.

PET scans provide additional clinical value but are costly and not universally accessible. Salehjahromi et al.1 developed an AI-based pipeline to synthesize PET images from diagnostic CT scans, demonstrating its potential clinical utility across various clinical tasks for lung cancer.

AML with RUNX1::RUNX1T1 Cooperating two Mutations Relapsed Quickly after Achieving CR.

BACKGROUND: Acute myeloid leukemia (AML) with t(8;21)(q22;q22.1); RUNX1::RUNX1T1 has a relatively favorable prognosis with a high complete remission rate and long disease-free survival. METHODS AND RESULTS: Here we describe a patient who had AML with t(8;21)(q22;q22.1); RUNX1::RUNX1T1. Cooperating mutations including KRAS and ASXL1, and with other abnormal karyotype del(17) and with a myelomonocytic differentiation. CONCLUSIONS: The patient relapsed despite achieving a morphologic complete remission (CR).

Analysis of clinical data of different endometrial pathological types in perimenopausal women with abnormal uterine bleeding.

Objective: Early detection and diagnosis are important for improving the therapeutic effect and quality of life in patients with endometrial cancer (EC). This study aimed to analyze the clinical data of different endometrial pathological types in perimenopausal women with abnormal uterine bleeding (AUB) in order to provide evidence for the prevention and early diagnosis of EC. Methods: A total of 462 perimenopausal women with AUB were enrolled in this prospective observational study. Endometrial biopsy was performed in patients with suspected endometrial lesions. According to the pathological examination results, the patients were divided into endometrial polyp group (EP) (n = 71), endometrial hyperplasia without atypia group (EH) (n = 59), atypical endometrial hyperplasia (AEH) (n = 36), and EC group (n = 27). The history risk factors and ultrasonic imaging characteristics of endometrium among the four groups were compared. Results: Twenty-seven women were diagnosed with EC (5.84%). The prevalence rate of AEH and EC in the group of 51- to 55-year-old women was significantly higher than that in the groups of 40- to 45-year-old women and of 46- to 50-year-old women (P < 0.05). The age, body mass index, and history of diabetes gradually increased with the development of endometrial pathological types. In addition, the correlation index of endometrial blood flow increased gradually, and the proportion of uneven endometrial echo, unclear endometrial-myometrial junction (EMJ), and ovarian cyst also increased gradually. However, no statistically significant difference was found when comparing endometrial thickness (ET) and endometrial volume (EV) among endometrial pathological groups (P > 0.05). The ET, EV, endometrial vascularization index, endometrial flow index, and vascularization flow index in the ovarian cyst group were significantly higher (P < 0.05), and the proportion of uneven endometrium echo and unclear EMJ were significantly higher compared with that in the non-ovarian cyst group (P < 0.05). Conclusions: The most common cause of perimenopausal women with AUB was benign endometrial lesions. However, women aged 51-55 years old with endometrial high risk factors and ovarian cyst should be alert to AEH and EC. Endometrial biopsy needs to be performed to determine endometrial malignancy in necessity.

Evaluation of Laparoscopic Colorectal Resection Among Elderly Individuals With Colorectal Malignancy: A Single-center Retrospective Analysis.

OBJECTIVE: The purpose of the current study was to statistically clarify the precise risk age in elderly patients undergoing colorectal surgery and to evaluate the safety and efficacy of laparoscopic colorectal resection in these patients. METHODS: Patients' clinical variables were extracted from the database of the Gastrointestinal Surgery Centre, Third Affiliated Hospital of Sun Yat-sen University, from 2015 to 2019. Logistic regression was conducted to identify independent risk factors of postoperative complications and ORs for each age. Curves of odds ratios (ORs) and CIs for each age were fitted by using a locally weighted scatterplot smoother, and a structural breakpoint was determined by the Chow test to identify a precise cutoff risk age for elderly patients. Comparison and subgroup analysis were conducted between surgical approach groups using the Student ttest and χ2 analysis. RESULTS: Locally weighted scatterplot smoother OR analysis manifested that patients aged 69 years old or older suffered a higher possibility of postoperative complications and should be defined as high-risk age. Comparison according to the high-risk age revealed laparoscopic colorectal surgery is better than laparotomic surgery for elderly individuals in terms of hospital stay (9.46 ± 5.96 vs 15.01 ± 6.34, P< 0.05), the incidence of intensive care unit transfer (4 vs 20, P< 0.05), and incidence of surgical site infection (15 vs 20, P< 0.05). Patients who underwent laparotomic surgery had a greater prevalence of Clavien-Dindo II/III complications (P< 0.05). These findings remained stable even after propensity matching. Furthermore, such superiority was proved especially significant for patients who underwent left-side colorectal resection. In addition, overall survival was improved in the laparoscopic surgery group, whereas no differences were observed in disease-free survival. CONCLUSION: In our study population, age 69 or older was a cutoff point age suggests a higher possibility of postoperative morbidity after colorectal surgery. Laparoscopic colorectal resection should be regarded as a superior therapeutic choice for these elderly individuals, especially for left-side colorectal surgeries.