Combined Metabolomics and Biochemical Analyses of Serum and Milk Revealed Parity-Related Metabolic Differences in Sanhe Dairy Cattle.

The production performance of dairy cattle is closely related to their metabolic state. This study aims to provide a comprehensive understanding of the production performance and metabolic features of Sanhe dairy cattle across different parities, with a specific focus on evaluating variations in milk traits and metabolites in both milk and serum. Sanhe dairy cattle from parities 1 to 4 (S1, n = 10; S2, n = 9; S3, n = 10; and S4, n = 10) at mid-lactation were maintained under the same feeding and management conditions. The milk traits, hydrolyzed milk amino acid levels, serum biochemical parameters, and serum free amino acid levels of the Sanhe dairy cattle were determined. Multiparous Sanhe dairy cattle (S2, S3, and S4) had a greater milk protein content, lower milk lactose content, and lower solids-not-fat content than primiparous Sanhe dairy cattle (S1). Moreover, S1 had a higher ratio of essential to total amino acids (EAAs/TAAs) in both the serum and milk. The serum biochemical results showed the lower glucose and total protein levels in S1 cattle were associated with milk quality. Furthermore, ultra-high-resolution high-performance liquid chromatography with tandem MS analysis (UPLC-MS/MS) identified 86 and 105 differential metabolites in the serum and milk, respectively, and these were mainly involved in amino acid, carbohydrate, and lipid metabolism. S1 and S2/S3/S4 had significantly different metabolic patterns in the serum and milk, and more vitamin B-related metabolites were significantly higher identified in S1 than in multiparous cattle. Among 36 shared differential metabolites in the serum and milk, 10 and 7 metabolites were significantly and strongly correlated with differential physiological indices, respectively. The differential metabolites identified were enriched in key metabolic pathways, illustrating the metabolic characteristics of the serum and milk from Sanhe dairy cattle of different parities. L-phenylalanine, dehydroepiandrosterone, and linoleic acid in the milk and N-acetylornithine in the serum could be used as potential marker metabolites to distinguish between Sanhe dairy cattle with parities of 1-4. In addition, a metabolic map of the serum and milk from the three aspects of carbohydrates, amino acids, and lipids was created for the further analysis and exploration of their relationships. These results reveal significant variations in milk traits and metabolites across different parities of Sanhe dairy cattle, highlighting the influence of parity on the metabolic profiles and production performance. Tailored nutritional strategies based on parity-specific metabolic profiles are recommended to optimize milk production and quality in Sanhe cattle.

Notch2 Regulates the Function of Bovine Follicular Granulosa Cells via the Wnt2/ß-Catenin Signaling Pathway.

Ovarian follicular GCs are strongly implicated in the growth, development, and atresia of ovarian follicles. The Wnt/ß-catenin and Notch signaling pathways participate in GC proliferation, differentiation, apoptosis, and steroid hormone production during follicular development. However, the crosstalk between Wnt and Notch signaling in GCs remains unclear. This study investigated this crosstalk and the roles of these pathways in apoptosis, cell cycle progression, cell proliferation, and steroid hormone secretion in bovine follicular GCs. The interaction between ß-catenin and Notch2 in GCs was assessed by overexpressing CTNNB1, which encodes ß-catenin. The results showed that inhibiting the Notch pathway by Notch2 silencing in GCs arrested the cell cycle, promoted apoptosis, reduced progesterone (P4) production, and inhibited the Wnt2-mediated Wnt/ß-catenin pathway in GCs. IWR-1 inhibited Wnt2/ß-catenin and Notch signaling, reduced GC proliferation, stimulated apoptosis, induced G1 cell cycle arrest, and reduced P4 production. CTNNB1 overexpression had the opposite effect and increased 17ß-estradiol (E2) production and Notch2 protein expression. Co-immunoprecipitation assays revealed that Notch2 interacted with ß-catenin. These results elucidate the crosstalk between the Wnt/ß-catenin and Notch pathways and the role of these pathways in bovine follicular GC development.

Transcriptomic Analysis for Diurnal Temperature Differences Reveals Gene-Regulation-Network Response to Accumulation of Bioactive Ingredients of Protocorm-like Bodies in Dendrobium officinale.

Dendrobium officinale Kimura et Migo (D. officinale) is one of the most important traditional Chinese medicinal herbs, celebrated for its abundant bioactive ingredients. This study demonstrated that the diurnal temperature difference (DIF) (T1: 13/13 °C, T2: 25/13 °C, and T3: 25/25 °C) was more favorable for high chlorophyll, increased polysaccharide, and total flavonoid contents compared to constant temperature treatments in D. officinale PLBs. The transcriptome analysis revealed 4251, 4404, and 4536 differentially expressed genes (DEGs) in three different comparisons (A: 25/13 °C vs. 13/13 °C, B: 13/13 °C vs. 25/25 °C, and C: 25/13 °C vs. 25/25 °C, respectively). The corresponding up-/down-regulated DEGs were 1562/2689, 2825/1579, and 2310/2226, respectively. GO and KEGG enrichment analyses of DEGs showed that the pathways of biosynthesis of secondary metabolites, carotenoid biosynthesis, and flavonoid biosynthesis were enriched in the top 20; further analysis of the sugar- and flavonol-metabolism pathways in D. officinale PLBs revealed that the DIF led to a differential gene expression in the enzymes linked to sugar metabolism, as well as to flavonol metabolism. Certain key metabolic genes related to ingredient accumulation were identified, including those involved in polysaccharide metabolism (SUS, SUT, HKL1, HGL, AMY1, and SS3) and flavonol (UGT73C and UGT73D) metabolism. Therefore, these findings indicated that these genes may play an important role in the regulatory network of the DIF in the functional metabolites of D. officinale PLBs. In a MapMan annotation of abiotic stress pathways, the DEGs with significant changes in their expression levels were mainly concentrated in the heat-stress pathways, including heat-shock proteins (HSPs) and heat-shock transcription factors (HSFs). In particular, the expression levels of HSP18.2, HSP70, and HSF1 were significantly increased under DIF treatment, which suggested that HSF1, HSP70 and HSP18.2 may respond to the DIF. In addition, they can be used as candidate genes to study the effect of the DIF on the PLBs of D. officinale. The results of our qPCR analysis are consistent with those of the transcriptome-expression analysis, indicating the reliability of the sequencing. The results of this study revealed the transcriptome mechanism of the DIF on the accumulation of the functional metabolic components of D. officinale. Furthermore, they also provide an important theoretical basis for improving the quality of D. officinale via the DIF in production.

Inhibition of catechol-O-methyltransferase (COMT) by heparin oligosaccharides with specific structures.

COMT inhibitors are commonly used to improve the effectiveness of levodopa in treating Parkinson's disease by inhibiting its conversion to 3-O-methyldopa. Because of the serious side effect of nitrocatechol COMT inhibitors, it is necessary to develop non-nitrocatechol COMT inhibitors with a higher safety profile. Heparin has been observed to bind to COMT. However, the exact functional significance of this interaction is not fully understood. In this study, the contribution of different substitution of heparin to its binding with COMT was investigated. In vitro and in vivo, heparin oligosaccharides can bind to COMT and inhibit its activity. Furthermore, we enriched the functional heparin oligosaccharides that bind to COMT and identified the sequence UA2S-GlcN(S/Ac)6(S/H)-UA2S-GlcNS6(S/H)-UA2(S/H)-GlcNS6S as the characteristic structural domain of these functional oligosaccharides. This study has elucidated the relationship between the structure of heparin oligosaccharides and their activity against COMT, providing valuable insights for the development of non-nitrocatechol COMT inhibitors with improved safety and efficacy.

Multitask deep learning for prediction of microvascular invasion and recurrence-free survival in hepatocellular carcinoma based on MRI images.

BACKGROUND AND AIMS: Accurate preoperative prediction of microvascular invasion (MVI) and recurrence-free survival (RFS) is vital for personalised hepatocellular carcinoma (HCC) management. We developed a multitask deep learning model to predict MVI and RFS using preoperative MRI scans. METHODS: Utilising a retrospective dataset of 725 HCC patients from seven institutions, we developed and validated a multitask deep learning model focused on predicting MVI and RFS. The model employs a transformer architecture to extract critical features from preoperative MRI scans. It was trained on a set of 234 patients and internally validated on a set of 58 patients. External validation was performed using three independent sets (n = 212, 111, 110). RESULTS: The multitask deep learning model yielded high MVI prediction accuracy, with AUC values of 0.918 for the training set and 0.800 for the internal test set. In external test sets, AUC values were 0.837, 0.815 and 0.800. Radiologists' sensitivity and inter-rater agreement for MVI prediction improved significantly when integrated with the model. For RFS, the model achieved C-index values of 0.763 in the training set and ranged between 0.628 and 0.728 in external test sets. Notably, PA-TACE improved RFS only in patients predicted to have high MVI risk and low survival scores (p < .001). CONCLUSIONS: Our deep learning model allows accurate MVI and survival prediction in HCC patients. Prospective studies are warranted to assess the clinical utility of this model in guiding personalised treatment in conjunction with clinical criteria.

OA-GAN: organ-aware generative adversarial network for synthesizing contrast-enhanced medical images.

Contrast-enhanced computed tomography (CE-CT) images are vital for clinical diagnosis of focal liver lesions (FLLs). However, the use of CE-CT images imposes a significant burden on patients due to the injection of contrast agents and extended shooting. Deep learning-based image synthesis models offer a promising solution that synthesizes CE-CT images from non-contrasted CT (NC-CT) images. Unlike natural images, medical image synthesis requires a specific focus on certain organs or localized regions to ensure accurate diagnosis. Determining how to effectively emphasize target organs poses a challenging issue in medical image synthesis. To solve this challenge, we present a novel CE-CT image synthesis model called, Organ-Aware Generative Adversarial Network (OA-GAN). The OA-GAN comprises an organ-aware (OA) network and a dual decoder-based generator. First, the OA network learns the most discriminative spatial features about the target organ (i.e. liver) by utilizing the ground truth organ mask as localization cues. Subsequently, NC-CT image and captured feature are fed into the dual decoder-based generator, which employs a local and global decoder network to simultaneously synthesize the organ and entire CECT image. Moreover, the semantic information extracted from the local decoder is transferred to the global decoder to facilitate better reconstruction of the organ in entire CE-CT image. The qualitative and quantitative evaluation on a CE-CT dataset demonstrates that the OA-GAN outperforms state-of-the-art approaches for synthesizing two types of CE-CT images such as arterial phase and portal venous phase. Additionally, subjective evaluations by expert radiologists and a deep learning-based FLLs classification also affirm that CE-CT images synthesized from the OA-GAN exhibit a remarkable resemblance to real CE-CT images.

Imaging Features of Biliary Adenofibroma With Malignant Transformation: A Case Report and Literature Review.

Biliary adenofibroma (BAF) is a rare benign tumor, but it has the potential for malignant transformation. The differentiation between benign and malignant forms of BAF before surgery is of great importance for clinical decision-making. We report a case of BAF with invasive carcinoma. The patient did not present any clinical symptoms but had a history of hepatitis B virus infection for more than twenty years. Magnetic resonance imaging (MRI) revealed a solid and cystic 4 cm mass in segment II of the liver exhibiting hypointense signals on T1-weighted images and intermediate-to-high intensity signals on T2-weighted images. Enhancement scanning revealed markedly rim-like enhancement on the arterial phase, with the left inter-hepatic artery as the tumor-feeding artery, and wash-out on the venous and delayed phases. To the best of our knowledge, BAF with invasive carcinoma is uncommon. Preoperative qualitative diagnosis based on imaging features can achieve the maximum benefit for patients.

Histiocytic necrotizing lymphadenitis with hemophagocytic lymphohistiocytosis in adults: A single-center analysis of 5 cases.

BACKGROUND: Histiocytic necrotizing lymphadenitis (HNL) is a self-limited inflammatory disease of unknown pathogenesis. A very small fraction of patients with HNL could develop hemophagocytic lymphohistiocytosis (HLH), a hyperinflammatory disorder. These patients are diagnosed as HNL with HLH (HNL-HLH). HNL-HLH in the pediatric population has been systemically studied, however, the clinical, laboratory, and radiological features and outcomes of adult patients with HNL-HLH remain to be explored. We aimed to explore the clinical, laboratory, and radiological features and outcomes of adult patients with HNL-HLH. METHODS: We collected the clinical data of patients with HNL-HLH admitted to the First Affiliated Hospital of Nanjing Medical University from October 2010 to June 2015. All the patients underwent lymph node biopsy and have a pathological diagnosis of HNL. The age, gender, clinical presentation, lymph node signs, laboratory findings and imaging data, and pathological findings of the patients were collected. RESULTS: In this study, we reported five adult patients with HNL-HLH. All five patients showed enlarged lymph nodes and prolonged fever. Laboratory findings were consistent with the diagnosis of HLH. 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) showed enlarged lymph nodes with increased FDG uptake and splenic hypermetabolism could be present. All the patients responded well to corticosteroids and had a good prognosis. Two of the five patients were diagnosed with systemic lupus erythematosus during the follow-up. CONCLUSIONS: Our study demonstrated that adult patients with HNL-HLH showed distinct clinical, laboratory, and radiological features. And the prognosis is good and patients could be managed with steroids and supportive care.

Improving impact of heparan sulfate on the endothelial glycocalyx abnormalities in atherosclerosis as revealed by glycan-protein interactome.

Endothelial dysfunction induced by oxidative stress is an early predictor of atherosclerosis, which can cause various cardiovascular diseases. The glycocalyx layer on the endothelial cell surface acts as a barrier to maintain endothelial biological function, and it can be impaired by oxidative stress. However, the mechanism of glycocalyx damage during the development of atherosclerosis remains largely unclear. Herein, we established a novel strategy to address these issues from the glycomic perspective that has long been neglected. Using countercharged fluorescence protein staining and quantitative mass spectrometry, we found that heparan sulfate, a major component of the glycocalyx, was structurally altered by oxidative stress. Comparative proteomics and protein microarray analysis revealed several new heparan sulfate-binding proteins, among which alpha-2-Heremans-Schmid glycoprotein (AHSG) was identified as a critical protein. The molecular mechanism of AHSG with heparin was characterized through several methods. A heparan analog could relieve atherosclerosis by protecting heparan sulfate from degradation during oxidative stress and by reducing the accumulation of AHSG at lesion sites. In the present study, the molecular mechanism of anti-atherosclerotic effect of heparin through interaction with AHSG was revealed. These findings provide new insights into understanding of glycocalyx damage in atherosclerosis and lead to the development of corresponding therapeutics.

Ferroptosis: a new mechanism of traditional Chinese medicine for cancer treatment.

Ferroptosis, distinct from apoptosis, is a novel cellular death pathway characterized by the build-up of lipid peroxidation and reactive oxygen species (ROS) derived from lipids within cells. Recent studies demonstrated the efficacy of ferroptosis inducers in targeting malignant cells, thereby establishing a promising avenue for combating cancer. Traditional Chinese medicine (TCM) has a long history of use and is widely used in cancer treatment. TCM takes a holistic approach, viewing the patient as a system and utilizing herbal formulas to address complex diseases such as cancer. Recent TCM studies have elucidated the molecular mechanisms underlying ferroptosis induction during cancer treatment. These studies have identified numerous plant metabolites and derivatives that target multiple pathways and molecular targets. TCM can induce ferroptosis in tumor cells through various regulatory mechanisms, such as amino acid, iron, and lipid metabolism pathways, which may provide novel therapeutic strategies for apoptosis-resistant cancer treatment. TCM also influence anticancer immunotherapy via ferroptosis. This review comprehensively elucidates the molecular mechanisms underlying ferroptosis, highlights the pivotal regulatory genes involved in orchestrating this process, evaluates the advancements made in TCM research pertaining to ferroptosis, and provides theoretical insights into the induction of ferroptosis in tumors using botanical drugs.

Distinct mechanisms underlying the therapeutic effects of low-molecular-weight heparin and chondroitin sulfate on Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder influenced by various factors, including age, genetics, and the environment. Current treatments provide symptomatic relief without impeding disease progression. Previous studies have demonstrated the therapeutic potential of exogenous heparin and chondroitin sulfate in PD. However, their therapeutic mechanisms and structure-activity relationships remain poorly understood. In this study, low-molecular-weight heparin (L-HP) and chondroitin sulfate (L-CS) exhibited favorable therapeutic effects in a mouse model of PD. Proteomics revealed that L-HP attenuated mitochondrial dysfunction through its antioxidant properties, whereas L-CS suppressed neuroinflammation by inhibiting platelet activation. Two glycosaminoglycan (GAG)-binding proteins, manganese superoxide dismutase (MnSOD2) and fibrinogen beta chain (FGB), were identified as potential targets of L-HP and L-CS, and we investigated their structure-activity relationships. The IdoA2S-GlcNS6S/GlcNAc6S unit in HP bound to SOD2, whereas the GlcA-GalNAc4S and GlcA-GalNAc4S6S units in CS preferred FGB. Furthermore, N-S and 2-O-S in L-HP, and 4-O-S, 6-O-S, and -COOH in L-CS contributed significantly to the binding process. These findings provide new insights and evidence for the development and use of glycosaminoglycan-based therapeutics for PD.

MSPA-DLA++: A Multi-Scale Phase Attention Deep Layer Aggregation for Lesion Detection in Multi-Phase CT Images.

Object detection using convolutional neural networks (CNNs) has achieved high performance and achieved state-of-the-art results with natural images. Compared to natural images, medical images present several challenges for lesion detection. First, the sizes of lesions vary tremendously, from several millimeters to several centimeters. Scale variations significantly affect lesion detection accuracy, especially for the detection of small lesions. Moreover, the effective extraction of temporal and spatial features from multi-phase CT images is also an important issue. In this paper, we propose a group-based deep layer aggregation method with multiphase attention for liver lesion detection in multi-phase CT images. The method, which is called MSPA-DLA++, is a backbone feature extraction network for anchor-free liver lesion detection in multi-phase CT images that addresses scale variations and extracts hidden features from such images. The effectiveness of the proposed method is demonstrated on public datasets (LiTS2017) and our private multiphase dataset. The results of the experiments show that MSPA-DLA++ can improve upon the performance of state-of-the-art networks by approximately 3.7%.

Natural isoflavone glabridin targets PI3Kγ as an adjuvant to increase the sensitivity of MDA-MB-231 to tamoxifen and DU145 to paclitaxel.

Glabridin is a natural isoflavone with estrogen receptor agonism and significant anti-tumor activity. Additionally, glabridin has a regulation effect on PI3K/AKT/mTOR pathway, but its exact target remains unclear. In this study, we evaluated the antitumor activity of glabridin against breast cancer and prostate cancer cells, and further clarified its targeting to PI3K. We found that glabridin could significantly inhibit the cell viability of human breast cancer and prostate cancer cell lines. It induced caspase activation cascade and cell apoptosis through decreasing the mitochondrial transmembrane potential and increasing the intracellular reactive oxygen species (ROS). Moreover, glabridin could attenuate epithelial-mesenchymal transition (EMT) progression by inhibiting cell migration. PharmMapper calculation showed that PI3Kγ might be the most potential target protein because of the highest Normal Fit score (0.9735) and z'-score (0.9797). Molecular docking and bio-layer interferometry (BLI) analysis further demonstrated the PI3Kγ targeting of glabridin. In vivo experiments showed that glabridin can effectively inhibit the tumor growth of breast cancer xenograft model, and does not show obvious hepatorenal toxicity. Moreover, glabridin could effectively promote the anti-proliferation and pro-apoptotic effects of tamoxifen on MDA-MB-231 cell and taxol on DU145 cell. Elucidating the targeting of glabridin to PI3K may lay a theoretical foundation for the structural derivatization of glabridin, which is expected to greatly promote the application and development of glabridin in the field of cancer therapy.

Downregulation of homeobox A1 in human granulosa cells is involved in diminished ovarian reserve through promoting cell apoptosis and mitochondrial dysfunction.

Granulosa cell apoptosis contributes to the occurrence of diminished ovarian reserve (DOR). HOXA1, belonging to the HOX gene family, is involved in regulating cancer cell apoptosis. However, whether HOXA1 participates in the granulosa cell apoptosis in DOR patients remains to be elucidated. In the current study, we demonstrated the differential transcriptomic landscape of granulosa cells in DOR patients compared to that in the controls and identified decreased expression of the HOXA1 gene. Meanwhile, we found that HOXA1 was a gonadotropin-response gene, in which FSH could promote its expression, whereas LH inhibited HOXA1 expression in human granulosa cells. CCK-8 assay, flow cytometry and TUNEL staining results showed that inhibition of endogenous HOXA1 expression promoted human granulosa cell apoptosis. Moreover, knockdown of HOXA1 increased Bax while reducing Bcl2 protein expression. Furthermore, we found a total of 947 differentially expressed genes (DEGs), including 426 upregulated genes and 521 downregulated genes using transcriptome sequencing technology. Enrichment analysis results showed that the DEGs were involved in apoptosis and mitochondrial function-related signaling pathways. Knockdown of HOXA1 impaired mitochondrial functions, exhibiting increased reactive oxygen species (ROS) and cytoplasmic Ca2+ levels, decreased mitochondrial membrane potential, ATP production and mitochondrial DNA (mtDNA) copy number, and abnormal mitochondrial cristae. Our findings demonstrated that aberrantly reduced HOXA1 expression induced granulosa cell apoptosis in DOR patients and impaired mitochondrial function, which highlighted the potential role of HOXA1 in the occurrence of DOR and provided new insight for the treatment of DOR.

Deep Learning Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Prognosis in Hepatocellular Carcinoma.

BACKGROUND: Vessels encapsulating tumor cluster (VETC) is a critical prognostic factor and therapeutic predictor of hepatocellular carcinoma (HCC). However, noninvasive evaluation of VETC remains challenging. PURPOSE: To develop and validate a deep learning radiomic (DLR) model of dynamic contrast-enhanced MRI (DCE-MRI) for the preoperative discrimination of VETC and prognosis of HCC. STUDY TYPE: Retrospective. POPULATION: A total of 221 patients with histologically confirmed HCC and stratified this cohort into training set (n = 154) and time-independent validation set (n = 67). FIELD STRENGTH/SEQUENCE: A 1.5 T and 3.0 T; DCE imaging with T1-weighted three-dimensional fast spoiled gradient echo. ASSESSMENT: Histological specimens were used to evaluate VETC status. VETC+ cases had a visible pattern (≥5% tumor area), while cases without any pattern were VETC-. The regions of intratumor and peritumor were segmented manually in the arterial, portal-venous and delayed phase (AP, PP, and DP, respectively) of DCE-MRI and reproducibility of segmentation was evaluated. Deep neural network and machine learning (ML) classifiers (logistic regression, decision tree, random forest, SVM, KNN, and Bayes) were used to develop nine DLR, 54 ML and clinical-radiological (CR) models based on AP, PP, and DP of DCE-MRI for evaluating VETC status and association with recurrence. STATISTICAL TESTS: The Fleiss kappa, intraclass correlation coefficient, receiver operating characteristic curve, area under the curve (AUC), Delong test and Kaplan-Meier survival analysis. P value <0.05 was considered as statistical significance. RESULTS: Pathological VETC+ were confirmed in 68 patients (training set: 46, validation set: 22). In the validation set, DLR model based on peritumor PP (peri-PP) phase had the best performance (AUC: 0.844) in comparison to CR (AUC: 0.591) and ML (AUC: 0.672) models. Significant differences in recurrence rates between peri-PP DLR model-predicted VETC+ and VETC- status were found. DATA CONCLUSIONS: The DLR model provides a noninvasive method to discriminate VETC status and prognosis of HCC patients preoperatively. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: Stage 2.

Structurally defined heparin octasaccharide domain for binding to SARS-CoV-2 Omicron BA.4/BA.5/BA.5.2 spike protein RBD.

Heparin, a bio-molecule with the highest negative charge density, is pharmaceutically important to prevent SARS-CoV-2 infection due to its strong competitive binding to spike protein compared with cellular heparan sulfate, which was confirmed as a co-receptor for virus-host cell interaction. Hence, the refined structural characterization of heparin targeting viral protein-HS interaction was significant for developing antiviral pharmaceuticals. In our study, heparin oligomers (dp ≥ 4) were prepared using heparinase I. The affinity oligosaccharides binding to Omicron spike protein RBD were separated by affinity chromatography and size exclusion chromatography. HILIC-ESI-FTMS was used for chain mapping analysis. The basic building blocks were analyzed and the binding domain sequence was produced by Seq-GAG software and further measured by SAX chromatography. As results, heparin octasaccharide was found with significantly higher binding ability than hexasaccharide and tetrasaccharide, and the octasaccharide [ΔUA-GlcNS6S-GlcA-GlcNS6S-IdoA2S-GlcNS6S-IdoA2S-GlcNS6S] with 12 sulfate groups showed high binding to RBD. The mechanism of this structurally well-defined octasaccharide binding to RBD was further investigated by molecular docking. The affinity energy of optimal pose was -6.8 kcal/mol and the basic amino acid residues in RBD sequence (Arg403, Arg452, Arg493 and His505) were identified as the major contribution factor to interacting with sulfate/carboxyl groups on saccharide chain. Our study demonstrated that heparin oligosaccharide with well-defined structure could be potentially developed as anti-SARS-CoV-2 drugs.

Effectiveness and safety analysis of titanium mesh grafting versus bone grafting in the treatment of spinal Tuberculosis: a systematic review and meta-analysis.

BACKGROUND: To systematically assess the safety and effectiveness of titanium mesh grafting compared with bone grafting in the treatment of spinal tuberculosis. METHODS: Electronic databases, including PubMed, Embase, Web of Science, and Cochrane Library, were searched from their inception until April 2023. The outcome indicators for patients treated with titanium mesh grafting or bone grafting for spinal tuberculosis include surgical duration, intraoperative blood loss, graft fusion time, American Spinal Injury Association (ASIA) Spinal Cord Injury Grade E assessment, VAS score, lumbar pain score, post-graft kyphotic angle, and postoperative complications. The Newcastle-Ottawa Scale (NOS) and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach were used for quality assessment and evidence grading of clinical studies. Funnel plots and Begg's test were employed for bias assessment. RESULTS: A total of 8 studies were finally included, comprising 523 patients, with 267 cases of titanium mesh fixation and 256 cases of bone grafting. The meta-analysis showed no significant statistical differences in surgical duration (Weighted Mean Difference (WMD) = -7.20, 95% Confidence Interval (CI): -28.06 to 13.67, P = 0.499), intraoperative blood loss (WMD = 16.22, 95% CI: -40.62 to 73.06, P = 0.576), graft fusion time (WMD = 0.97, 95% CI: -0.88 to 2.81, P = 0.304), ASIA Spinal Cord Injury Grade E assessment (Relative Risk (RR) = 1.03, 95% CI: 0.97 to 1.09, P = 0.346), and overall complications (RR = 0.87, 95% CI: 0.49 to 1.55, P = 0.643). Differences in VAS score, ODI lumbar pain score, and post-graft kyphotic angle between the titanium mesh grafting group and the bone grafting group were not significant within the 95% CI range. The rate of postoperative implant subsidence was slightly lower in bone grafting than in titanium mesh grafting (RR = 9.30, 95% CI: 1.05 to 82.22, P = 0.045). CONCLUSIONS: Both bone grafting and titanium mesh grafting are effective and safe for the surgery, with no significant statistical differences in the results. Considering the limitations of the present study, large-scale randomized controlled trials are warranted to further verify the reliability of this finding.

Contrastive Learning for Preoperative Early Recurrence Prediction of Hepatocellular Carcinoma with Liver CT Image and Tumor Mask.

High early recurrence (ER) rate is the main factor leading to the poor outcome of patients with hepatocellular carcinoma (HCC). Accurate preoperative prediction of ER is thus highly desired for HCC treatment. Many radiomics solutions have been proposed for the preoperative prediction of HCC using CT images based on machine learning and deep learning methods. Nevertheless, most current radiomics approaches extract features only from segmented tumor regions that neglect the liver tissue information which is useful for HCC prognosis. In this work, we propose a deep prediction network based on CT images of full liver combined with tumor mask that provides tumor location information for better feature extraction to predict the ER of HCC. While, due to the complex imaging characteristics of HCC, the image-based ER prediction methods suffer from limited capability. Therefore, on the one hand, we propose to employ supervised contrastive loss to jointly train the deep prediction model with cross-entropy loss to alleviate the problem of intra-class variation and inter-class similarity of HCC. On the other hand, we incorporate the clinical data to further improve the prediction ability of the model. Experiments are extensively conducted to verify the effectiveness of our proposed deep prediction model and the contribution of liver tissue for prognosis assessment of HCC.

Spatial Attention-Guided Generative Adversarial Network for Synthesizing Contrast-enhanced Computed Tomography Images.

Compared to non-contrast computed tomography (NC-CT) scans, contrast-enhanced (CE) CT scans provide more abundant information about focal liver lesions (FLLs), which play a crucial role in the FLLs diagnosis. However, CE-CT scans require patient to inject contrast agent into the body, which increase the physical and economic burden of the patient. In this paper, we propose a spatial attention-guided generative adversarial network (SAG-GAN), which can directly obtain corresponding CE-CT images from the patient's NC-CT images. In the SAG-GAN, we devise a spatial attention-guided generator, which utilize a lightweight spatial attention module to highlight synthesis task-related areas in NC-CT image and neglect unrelated areas. To assess the performance of our approach, we test it on two tasks: synthesizing CE-CT images in arterial phase and portal venous phase. Both qualitative and quantitative results demonstrate that SAG-GAN is superior to existing GANs-based image synthesis methods.

Sea Cucumber Peptides Ameliorate DSS-Induced Ulcerative Colitis: The Role of the Gut Microbiota, the Intestinal Barrier, and Macrophage Polarization.

The incidence of ulcerative colitis (UC) is increasing annually. There are few treatments for UC patients, and some drugs have serious side effects. Sea cucumber peptide (SCP) has anti-inflammatory, antioxidant and other biological activities, and various sea cucumber species are in pharmaceutical development. However, relevant studies on the effects of SCP on UC progression are still lacking. In this study, a mouse model of acute colitis was induced by 3% dextran sulfate (DSS), and the effect of 500 mg/kg SCP on colitis was investigated. The results showed that SCP can alleviate DSS-induced colon damage and intestinal barrier damage. SCP significantly inhibited the expression of inflammatory factors and oxidative stress in UC mice. SCP reversed the intestinal microbiota dysregulation induced by DSS, inhibited the growth of Sutterella, Prevotella_9 and Escherichia-Shigella harmful bacteria, and increased the abundance of Lachnospiraceae_NK4A136_group. At the same time, SCP treatment significantly inhibited the LPS-induced polarization of M1 macrophages, which may be mediated by two monopeptides, IPGAPGVP and TGPIGPPGSP, via FPR2. In conclusion, SCP can protect against colitis by modulating the intestinal microbiota composition and the intestinal barrier and inhibiting the polarization of M1 macrophages.